573 results match your criteria Academy Of Management Learning & Education[Journal]


Predictive ability of the American Society of Anaesthesiologists physical status classification system on health-related quality of life of patients after total hip replacement: comparisons across eight EQ-5D-3L value sets.

BMC Musculoskelet Disord 2020 Jul 6;21(1):441. Epub 2020 Jul 6.

Health Outcomes and Economic Evaluation Research Group, Stockholm Centre for Healthcare Ethics, Department of Learning Informatics, Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden.

Background: American Society of Anaesthesiologists (ASA) physical status classification system and its association with postoperative outcomes has been studied in different diseases. However, there is a paucity of studies on the relationship between ASA class and postoperative health-related quality of life (HRQoL) outcomes following total hip replacement (THR). The aim of this study was to assess the discriminative abilities of EQ-5D-3L value sets from Sweden, Germany, Denmark and the United Kingdom in relation to ASA classes and these value sets' abilities to show the predictive performance of ASA classes on HRQoL among THR patients in Sweden. Read More

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http://dx.doi.org/10.1186/s12891-020-03399-8DOI Listing

Modeling the ecological status response of rivers to multiple stressors using machine learning: A comparison of environmental DNA metabarcoding and morphological data.

Water Res 2020 Jun 15;183:116004. Epub 2020 Jun 15.

State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing, 100012, China.

Understanding the ecological status response of rivers to multiple stressors is a precondition for river restoration and management. However, this requires the collection of appropriate data, including environmental variables and the status of aquatic organisms, and analysis via a suitable model that captures the nonlinear relationships between ecological status and various stressors. The morphological approach has been the standard data collection method employed for establishing the status of aquatic organisms. Read More

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http://dx.doi.org/10.1016/j.watres.2020.116004DOI Listing

Integrating handover curricula in medical school.

Clin Teach 2020 Jul 3. Epub 2020 Jul 3.

Department of Anesthesiology and Pain Management, UT Southwestern Medical School, Dallas, Texas, USA.

Background: Transitions of care are a patient-safety priority. Constructs such as SBAR (situation, background, assessment, recommendation) and I-PASS (illness severity, patient summary, action list, situation awareness, synthesis by receiver) have been used to teach the benefit of structured handovers and have demonstrated an impact in simulated and clinical environments. Despite this, there is still a lack of literature describing handover training for medical students that allows early and sustained knowledge and skill acquisition. Read More

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http://dx.doi.org/10.1111/tct.13181DOI Listing

Pyramid attention recurrent networks for real-time guidewire segmentation and tracking in intraoperative X-ray fluoroscopy.

Comput Med Imaging Graph 2020 May 25;83:101734. Epub 2020 May 25.

State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; CAS Center for Excellence in Brain Science and Intelligence Technology, Beijing 100190, China; School of Artificial Intelligence, University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address:

In endovascular and cardiovascular surgery, real-time and accurate segmentation and tracking of interventional instruments can aid in reducing radiation exposure, contrast agent and processing time. Nevertheless, this task often comes with the challenges of the elongated deformable structures with low contrast in noisy X-ray fluoroscopy. To address these issues, a novel efficient network architecture, termed pyramid attention recurrent networks (PAR-Net), is proposed for real-time guidewire segmentation and tracking. Read More

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http://dx.doi.org/10.1016/j.compmedimag.2020.101734DOI Listing

Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review.

Biomed Res Int 2020 10;2020:9867872. Epub 2020 Jun 10.

"Grigore T. Popa" University of Medicine, Iasi, Romania.

Background: The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation. Published studies were presented from two points of view: What medical aspects were covered? What AI/ML algorithms have been used?

Methods: We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT). Sixty-nine studies were split into three categories: AI/ML and HD, PD, and KT, respectively. Read More

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http://dx.doi.org/10.1155/2020/9867872DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7303737PMC

Contributions of information and communications technology to future health systems and Universal Health Coverage: application of Japan's experiences.

Health Res Policy Syst 2020 Jun 26;18(1):73. Epub 2020 Jun 26.

Department of Health Policy and Management, School of Medicine, Keio University, Tokyo, Japan.

Background: Demographic changes in the pattern of disease burden, escalating health expenditures and inequitable access to healthcare are global challenges. Irrespective of their level of development, all countries need to reform their health systems to prepare for the future emerging health needs, in order to meet their commitments of health systems strengthening, universal health coverage (UHC) and explicit targets in the Sustainable Development Goals (SDGs). We propose three core principles for the future health system as described herein. Read More

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http://dx.doi.org/10.1186/s12961-020-00585-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7318469PMC

Toward Optimal Heparin Dosing by Comparing Multiple Machine Learning Methods: Retrospective Study.

JMIR Med Inform 2020 Jun 22;8(6):e17648. Epub 2020 Jun 22.

Department of Critical Care Medicine, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical, Beijing, China.

Background: Heparin is one of the most commonly used medications in intensive care units. In clinical practice, the use of a weight-based heparin dosing nomogram is standard practice for the treatment of thrombosis. Recently, machine learning techniques have dramatically improved the ability of computers to provide clinical decision support and have allowed for the possibility of computer generated, algorithm-based heparin dosing recommendations. Read More

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http://dx.doi.org/10.2196/17648DOI Listing

Insulin autoimmune syndrome.

Endocrinol Diabetes Metab Case Rep 2020 Jun 4;2020. Epub 2020 Jun 4.

Laboratory of Inherited Endocrine Disorders, Endocrinology Research Centre (ERC), Moscow, Russia.

Summary: Insulin autoimmune syndrome (Hirata's disease) is a disorder caused by development of autoantibodies to insulin and manifested by hypoglycaemic syndrome. The overwhelming majority of physicians do not include it in the differential diagnosis of hypoglycaemic states because of a misconception of an extremely low prevalence of this condition. This results in unnecessary drug therapy and unjustified surgical interventions in patients that otherwise would be successfully treated conservatively. Read More

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http://dx.doi.org/10.1530/EDM-19-0159DOI Listing

A predictive analytics model for differentiating between transient ischemic attacks (TIA) and its mimics.

BMC Med Inform Decis Mak 2020 Jun 18;20(1):112. Epub 2020 Jun 18.

Department of Neurology, Division of Cerebrovascular Diseases, Geisinger Medical Center, 100 N Academy Ave, Danville, PA, 17822, USA.

Background: Transient ischemic attack (TIA) is a brief episode of neurological dysfunction resulting from cerebral ischemia not associated with permanent cerebral infarction. TIA is associated with high diagnostic errors because of the subjective nature of findings and the lack of clinical and imaging biomarkers. The goal of this study was to design and evaluate a novel multinomial classification model, based on a combination of feature selection mechanisms coupled with logistic regression, to predict the likelihood of TIA, TIA mimics, and minor stroke. Read More

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http://dx.doi.org/10.1186/s12911-020-01154-6DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7302339PMC

In situ simulation training in helicopter emergency medical services: feasible for on-call crews?

Adv Simul (Lond) 2020 15;5. Epub 2020 Jun 15.

Department of Research, Norwegian Air Ambulance Foundation, Drøbak, Norway.

Simulation-based training of emergency teams offers a safe learning environment in which training in the management of the critically ill patient can be planned and practiced without harming the patient. We developed a concept for in situ simulation that can be carried out during on-call time. The aim of this study is to investigate the feasibility of introducing in situ, simulation-based training for the on-call team on a busy helicopter emergency medical service (HEMS) base. Read More

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http://dx.doi.org/10.1186/s41077-020-00126-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7294664PMC

Encoding primitives generation policy learning for robotic arm to overcome catastrophic forgetting in sequential multi-tasks learning.

Neural Netw 2020 Jun 5;129:163-173. Epub 2020 Jun 5.

Cyber and Big Data Research Laboratory, Edinburgh Napier University, Edinburgh EH11 4BN, UK.

Continual learning, a widespread ability in people and animals, aims to learn and acquire new knowledge and skills continuously. Catastrophic forgetting usually occurs in continual learning when an agent attempts to learn different tasks sequentially without storing or accessing previous task information. Unfortunately, current learning systems, e. Read More

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http://dx.doi.org/10.1016/j.neunet.2020.06.003DOI Listing

COVID-19 pandemic: Practical considerations on the organization of an allergy clinic - an EAACI/ARIA Position Paper.

Allergy 2020 Jun 12. Epub 2020 Jun 12.

Transylvania University, Brasov, Romania.

Background: The Coronavirus disease 2019 (COVID-19) has evolved as a pandemic infectious disease transmitted by the severe acute respiratory syndrome coronavirus (SARS-CoV-)2. Allergists and other health care providers (HCPs) in the field of allergies and associated airway diseases are in the front line, taking care of patients potentially infected with SARS-CoV-2. Hence, strategies and practices to minimize risks of infection for both HCPs and treated patients have to be developed and followed by allergy clinics. Read More

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http://dx.doi.org/10.1111/all.14453DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7323448PMC

Diabetes self-management education and support in adults with type 2 diabetes: A consensus report of the American Diabetes Association, the Association of Diabetes Care and Education Specialists, the Academy of Nutrition and Dietetics, the American Academy of Family Physicians, the American Academy of PAs, the American Association of Nurse Practitioners, and the American Pharmacists Association.

JAAPA 2020 Jul;33(7):1-20

Margaret A. Powers is a senior consultant with the nutrition practice and evaluation services at HealthPartners in Bloomington, Minn., and at the time this article was started, was a research scientist at the International Diabetes Center at Park Nicollet Helath Services in Minneapolis, Minn. Joan K. Bardsley is an assistant vice president of research and nursing integration with Medstar Health Research Institute and MedStar Health System Nursing in Hyattsville and Columbia, Md. Marjorie Cypress is an independent consultant in Albuquerque, N.M. Martha M. Funnell is an emeritus research scientist in the Department of Learning Health Science at the University of Michigan Medical School in Ann Arbor, Mich. Dixie Harms is a family NP at MercyOne Clive (Iowa) Internal Medicine. Amy Hess-Fischl is program manager and diabetes care and education specialist in the Section of Adult and Pediatric Endocrinology, Diabetes, and Metabolism at the University of Chicago in Chicago, Ill. Beulette Hooks is at Martin Army Community Hospital in Fort Benning, Ga. Diana Isaacs is an endocrine clinical pharmacy specialist at the Cleveland (Ohio) Clinic Diabetes Center. Ellen D. Mandel is program director and a professor in the PA program at Johnson & Wales University in Providence, R.I. Melinda D. Maryniuk is the owner of Maryniuk & Associates in Boston, Mass. Anna Norton is chief executive officer of DiabetesSisters in Chicago, Ill. Joanne Rinker is director of practice and content development in the science and practice department at the Association of Diabetes Care & Education Specialists in Chicago, Ill. Linda M. Siminerio is a professor of medicine and nursing, health and community systems at the University of Pittsburgh in Pittsburgh, Pa. Sacha Uelmen is director of diabetes education and prevention programs at the Association of Diabetes Care & Education Specialists in Chicago, Ill. This article was funded by the ADA and the Association of Diabetes Care & Education Specialists. Margaret A. Powers discloses research funding from Abbott Nutrition, is a senior advisor for ADA's Nutrition Interest Group, and is a member of ADA/American Heart Association Science Advisory Group for Know Diabetes by Heart. Joan K. Bardsley reports being a past chair of the Certification Board for Diabetes Care and Education, is the program chair for the Association of Diabetes Care & Education Specialists annual meeting, and has been a consultant to Joslin Diabetes Center. Martha M. Funnell is on an advisory board of Eli Lilly. Dixie Harms is the treasurer for the American Academy of Nurse Practitioners Certification Board of Commissioners and Vice President of the American Nurse Practitioner Foundation. Amy Hess-Fischl reports receiving an honorarium from ADA as an Education Recognition Program auditor and is a participant in a speakers bureau sponsored by Abbott Diabetes Care and Xeris. Diana Isaacs reports being a participant in a speakers bureau/consultant for Xeris Pharmaceuticals, Novo Nordisk, Dexcom, and Lifescan. Melinda D. Maryniuk reports being a paid consultant of Diabetes-What to Know, Arkray, and DayTwo. Anna Norton reports being a participant in speakers bureaus sponsored by Boehringer Ingelheim, Novo Nordisk, and Xeris. Linda M. Siminerio reports research grant funding from Becton Dickinson. Sacha Uelmen has received honoraria from ADA. The authors have disclosed no other potential conflicts of interest, financial or otherwise.

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http://dx.doi.org/10.1097/01.JAA.0000668828.47294.2aDOI Listing

Radiomics in liver diseases: Current progress and future opportunities.

Liver Int 2020 Jun 9. Epub 2020 Jun 9.

Key Laboratory of Molecular Imaging, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Liver diseases, a wide spectrum of pathologies from inflammation to neoplasm, have become an increasingly significant health problem worldwide. Noninvasive imaging plays a critical role in the clinical workflow of liver diseases, but conventional imaging assessment may provide limited information. Accurate detection, characterization and monitoring remain challenging. Read More

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http://dx.doi.org/10.1111/liv.14555DOI Listing

The power of last fixation: Biasing simple choices by gaze-contingent manipulation.

Acta Psychol (Amst) 2020 Jun 5;208:103106. Epub 2020 Jun 5.

School of Management, Zhejiang University of Technology, Hangzhou, China.

Among the established findings in eye movement during decision-making, decision-makers are likely to choose the last fixated option, and this phenomenon has proven robust. However, the causal link between last fixation and choices requires further examination. In Study 1 (N = 40), a gaze-contingent manipulation paradigm was developed by controlling the timing of decision prompts to manipulate the last fixation. Read More

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http://dx.doi.org/10.1016/j.actpsy.2020.103106DOI Listing

A collaborative online AI engine for CT-based COVID-19 diagnosis.

medRxiv 2020 May 19. Epub 2020 May 19.

School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan 430074, China.

Artificial intelligence can potentially provide a substantial role in streamlining chest computed tomography (CT) diagnosis of COVID-19 patients. However, several critical hurdles have impeded the development of robust AI model, which include deficiency, isolation, and heterogeneity of CT data generated from diverse institutions. These bring about lack of generalization of AI model and therefore prevent it from applications in clinical practices. Read More

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http://dx.doi.org/10.1101/2020.05.10.20096073DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7273252PMC

How CEO Ethical Leadership Influences Top Management Team Creativity: Evidence From China.

Front Psychol 2020 21;11:748. Epub 2020 May 21.

School of Management, Qilu University of Technology (Shandong Academy of Sciences), Jinan, China.

The creative thinking and ability of top management team (TMT) members is important in coping with rapid changes in the external environment and improving the competitive advantage of an organization. This research focuses on the CEO-TMT interface to explain how CEOs influence TMT characteristics, which in turn affects TMT outcomes. Based on social learning theory, this study examines the associations among CEO ethical leadership, TMT cohesion, and TMT creativity in a Chinese context using a total of 91 TMTs. Read More

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http://dx.doi.org/10.3389/fpsyg.2020.00748DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7253678PMC

The magnitude and drivers of harmful algal blooms in China's lakes and reservoirs: A national-scale characterization.

Water Res 2020 Aug 14;181:115902. Epub 2020 May 14.

School of Geography and the Environment, University of Oxford, Oxford, OX1 3QY, United Kingdom.

Harmful algal blooms (HABs) can have dire repercussions on aquatic wildlife and human health, and may negatively affect recreational uses, aesthetics, taste, and odor in drinking water. The factors that influence the occurrence and magnitude of harmful algal blooms and toxin production remain poorly understood and can vary in space and time. It is within this context that we use machine learning (ML) and two 14-year (2005-2018) data sets on water quality and meteorological conditions of China's lakes and reservoirs to shed light on the magnitude and associated drivers of HAB events. Read More

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http://dx.doi.org/10.1016/j.watres.2020.115902DOI Listing

Quality of primary health care in China: challenges and recommendations.

Lancet 2020 06;395(10239):1802-1812

National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; Fuwai Hospital, Chinese Academy of Medical Sciences, Shenzhen, China. Electronic address:

China has substantially increased financial investment and introduced favourable policies for strengthening its primary health care system with core responsibilities in preventing and managing chronic diseases such as hypertension and emerging infectious diseases such as coronavirus disease 2019 (COVID-19). However, widespread gaps in the quality of primary health care still exist. In this Review, we aim to identify the causes for this poor quality, and provide policy recommendations. Read More

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http://dx.doi.org/10.1016/S0140-6736(20)30122-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7272159PMC

Coronavirus Disease (COVID-19): A Machine Learning Bibliometric Analysis.

In Vivo 2020 Jun;34(3 Suppl):1613-1617

Department of Oral and Maxillo Facial Sciences, Policlinico Umberto I, "Sapienza" University of Rome, Rome, Italy.

Background/aim: To evaluate the research trends in coronavirus disease (COVID-19).

Materials And Methods: A bibliometric analysis was performed using a machine learning bibliometric methodology. Information regarding publication outputs, countries, institutions, journals, keywords, funding and citation counts was retrieved from Scopus database. Read More

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http://dx.doi.org/10.21873/invivo.11951DOI Listing

EQ-5D-Y-5L as a patient-reported outcome measure in psychiatric inpatient care for children and adolescents - a cross-sectional study.

Health Qual Life Outcomes 2020 Jun 3;18(1):164. Epub 2020 Jun 3.

Health Outcomes and Economic Evaluation Research Group, Stockholm Centre for Healthcare Ethics, Department of Learning, Informatics, Management and Ethics, Karolinska Institutet, Tomtebodavägen 18 A, SE-171 77, Stockholm, Sweden.

Background: Psychiatric disorders have a major individual and societal impact. Until now, the association between health-related quality of life and physical disorders has been far more investigated than the association with psychiatric disorders. Patient-reported outcome measures makes it possible to capture the patient perspective to improve treatments and evaluate treatment outcomes. Read More

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http://dx.doi.org/10.1186/s12955-020-01366-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7268241PMC

Informing children of their parent's illness: A systematic review of intervention programs with child outcomes in all health care settings globally from inception to 2019.

PLoS One 2020 26;15(5):e0233696. Epub 2020 May 26.

Academic Primary Health Care Center, Region Stockholm, Stockholm, Sweden.

Introduction: Children are impacted when parents are ill. This systematic review gives an overview of the current state of research and extracts what children and parents found helpful in the interventions aimed at informing children of their parent's illness.

Methods: This review was registered with PROSPERO and conducted in accordance with PRISMA guidelines. Read More

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0233696PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7250450PMC

Artificial Intelligence-Assisted System in Postoperative Follow-up of Orthopedic Patients: Exploratory Quantitative and Qualitative Study.

J Med Internet Res 2020 May 26;22(5):e16896. Epub 2020 May 26.

Department of Orthopedic Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Science and Peking Union Medical College, Beijing, China.

Background: Patient follow-up is an essential part of hospital ward management. With the development of deep learning algorithms, individual follow-up assignments might be completed by artificial intelligence (AI). We developed an AI-assisted follow-up conversational agent that can simulate the human voice and select an appropriate follow-up time for quantitative, automatic, and personalized patient follow-up. Read More

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http://dx.doi.org/10.2196/16896DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284488PMC

Deep learning from label proportions with labeled samples.

Neural Netw 2020 Aug 7;128:73-81. Epub 2020 May 7.

School of Economics and Management, University of Chinese Academy of Sciences, Beijing, 100190, China; Research Center on Fictitious Economy and Data Science, Chinese Academy of Sciences, Beijing 100190, China; Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences, Beijing 100190, China.

Learning from label proportions (LLP), where the training data is in form of bags, and only the proportions of classes in each bag are available, has attracted wide interest in machine learning community. In general, most LLP algorithms adopt random sampling to obtain the proportional information of different categories, which correspondingly obtains some labeled samples in each bag. However, LLP training process always fails to leverage these labeled samples, which may contain essential data distribution information. Read More

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http://dx.doi.org/10.1016/j.neunet.2020.04.026DOI Listing

Differentiation of Treatment-Related Effects from Glioma Recurrence Using Machine Learning Classifiers Based Upon Pre-and Post-Contrast T1WI and T2 FLAIR Subtraction Features: A Two-Center Study.

Cancer Manag Res 2020 7;12:3191-3201. Epub 2020 May 7.

Institute of Cancer and Basic Medicine (ICBM), Chinese Academy of Sciences, Hangzhou, People's Republic of China.

Purpose: We propose three support vector machine (SVM) classifiers, using pre-and post-contrast T2 fluid-attenuated inversion recovery (FLAIR) subtraction and/or pre-and post-contrast T1WI subtraction, to differentiate treatment-related effects (TRE) from glioma recurrence.

Materials And Methods: Fifty-six postoperative high-grade glioma patients with suspicious progression after radiotherapy and chemotherapy from two centers were studied. Pre-and post-contrast T1WI and T2 FLAIR were collected. Read More

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http://dx.doi.org/10.2147/CMAR.S244262DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7213892PMC

Cardiovascular Impairment in COVID-19: Learning From Current Options for Cardiovascular Anti-Inflammatory Therapy.

Front Cardiovasc Med 2020 30;7:78. Epub 2020 Apr 30.

Department of Cardiology, Peking Union Medical College Hospital, Peking Union Medical College & Chinese Academy of Medical Science, Beijing, China.

In December 2019, Coronavirus Disease 2019 (COVID-19) caused by SARS-CoV-2, occurred in China and has currently led to a global pandemic. In addition to respiratory involvement, COVID-19 was also associated with significant multiple organ dysfunction syndrome (MODS). Cardiovascular impairment has been observed and is now drawing growing attention. Read More

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http://dx.doi.org/10.3389/fcvm.2020.00078DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7203508PMC

Use statistical machine learning to detect nutrient thresholds in Microcystis blooms and microcystin management.

Harmful Algae 2020 Apr 23;94:101807. Epub 2020 Apr 23.

Chongqing Key Laboratory of Big Data and Intelligent Computing, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China; CAS Key Lab on Reservoir Environment, Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing 400714, China.

The frequency of toxin-producing cyanobacterial blooms has increased in recent decades due to nutrient enrichment and climate change. Because Microcystis blooms are related to different environmental conditions, identifying potential nutrient control targets can facilitate water quality managers to reduce the likelihood of microcystins (MCs) risk. However, complex biotic interactions and field data limitations have constrained our understanding of the nutrient-microcystin relationship. Read More

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http://dx.doi.org/10.1016/j.hal.2020.101807DOI Listing

Preliminary pragmatic lessons from the SARS-CoV-2 pandemic from France.

Anaesth Crit Care Pain Med 2020 May 13. Epub 2020 May 13.

Service d'Anesthésie-Réanimation & Médecine Péri-Opératoire, Hôpitaux Universitaires de Strasbourg-FMTS, Université de Strasbourg, Strasbourg, France. Electronic address:

The first wave of the SARS-CoV-2 pandemic required an unprecedented and historic increase in critical care capacity on a global scale in France. Authors and members from the ACUTE and REANIMATION committees of the French Society of Anaesthesia and Intensive Care (SFAR) wished to share experience and insights gained during the first weeks of this pandemic. These were summarised following the World Health Organization Response Checklist and detailed according to the subsequent subheadings: 1. Read More

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http://dx.doi.org/10.1016/j.accpm.2020.05.005DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7217765PMC

Comparison of surgical cricothyroidotomy training: a randomized controlled trial of a swine model versus an animated robotic manikin model.

Trauma Surg Acute Care Open 2020 26;5(1):e000431. Epub 2020 Apr 26.

Department of Surgery, Johns Hopkins School of Medicine, Baltimore, Maryland, United States.

Background: Airway obstruction remains a preventable cause of death on the battlefield. Surgical cricothyroidotomy is an essential skill for immediate airway management in trauma. Training for surgical cricothyroidotomy has been undertaken using simulators, cadavers or animal models. Read More

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http://dx.doi.org/10.1136/tsaco-2019-000431DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7204537PMC

Vicarious Learning: How Entrepreneurs Enhance a Firm's International Competitiveness Through Learning From Interlocking Director Network Partners.

Front Psychol 2020 21;11:689. Epub 2020 Apr 21.

School of Hotel and Tourism Management, Hong Kong Polytechnic University, Hung Hom, Hong Kong.

Applying the lens of entrepreneurial psychology, this paper examines vicarious learning as an approach that entrepreneurs can use to overcome external uncertainty of overseas investments by accumulating international know-how and experience through interlocking director connections with other experienced companies. Through the analysis of a sample of Chinese companies, our findings suggest that entrepreneurs obtaining foreign experience from interlocking partners can significantly promote their firm's international growth when investing in the same country, and that this positive effect is significant in relation to both first-degree and second-degree connections. We further find that, if an entrepreneur makes a connection with an interlocking partner in the same industry, it enhances their knowledge absorption, thereby providing a positive moderating effect, while investing in a country with a strong degree of openness weakens the effect of knowledge application, and thus plays a negative moderating role. Read More

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http://dx.doi.org/10.3389/fpsyg.2020.00689DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187782PMC

Species Classification for Neuroscience Literature Based on Span of Interest Using Sequence-to-Sequence Learning Model.

Front Hum Neurosci 2020 21;14:128. Epub 2020 Apr 21.

Research Center for Brain-Inspired Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Large-scale neuroscience literature call for effective methods to mine the knowledge from species perspective to link the brain and neuroscience communities, neurorobotics, computing devices, and AI research communities. Structured knowledge can motivate researchers to better understand the functionality and structure of the brain and link the related resources and components. However, the abstracts of massive scientific works do not explicitly mention the species. Read More

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http://dx.doi.org/10.3389/fnhum.2020.00128DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7187631PMC

Incorporating machine learning and social determinants of health indicators into prospective risk adjustment for health plan payments.

BMC Public Health 2020 May 1;20(1):608. Epub 2020 May 1.

Center for Primary Care, Harvard Medical School, Boston, USA.

Background: Risk adjustment models are employed to prevent adverse selection, anticipate budgetary reserve needs, and offer care management services to high-risk individuals. We aimed to address two unknowns about risk adjustment: whether machine learning (ML) and inclusion of social determinants of health (SDH) indicators improve prospective risk adjustment for health plan payments.

Methods: We employed a 2-by-2 factorial design comparing: (i) linear regression versus ML (gradient boosting) and (ii) demographics and diagnostic codes alone, versus additional ZIP code-level SDH indicators. Read More

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http://dx.doi.org/10.1186/s12889-020-08735-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7195714PMC

Development and validation of an interpretable deep learning framework for Alzheimer's disease classification.

Brain 2020 Jun;143(6):1920-1933

Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA.

Alzheimer's disease is the primary cause of dementia worldwide, with an increasing morbidity burden that may outstrip diagnosis and management capacity as the population ages. Current methods integrate patient history, neuropsychological testing and MRI to identify likely cases, yet effective practices remain variably applied and lacking in sensitivity and specificity. Here we report an interpretable deep learning strategy that delineates unique Alzheimer's disease signatures from multimodal inputs of MRI, age, gender, and Mini-Mental State Examination score. Read More

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http://dx.doi.org/10.1093/brain/awaa137DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7296847PMC

Arctic avian predators synchronise their spring migration with the northern progression of snowmelt.

Sci Rep 2020 Apr 29;10(1):7220. Epub 2020 Apr 29.

Max Planck Institute of Animal Behavior, Department of Migration, Am Obstberg 1, Radolfzell, 78315, Germany.

Migratory species display a range of migration patterns between irruptive (facultative) to regular (obligate), as a response to different predictability of resources. In the Arctic, snow directly influences resource availability. The causes and consequences of different migration patterns of migratory species as a response to the snow conditions remains however unexplored. Read More

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http://dx.doi.org/10.1038/s41598-020-63312-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7190624PMC

Profile of cases discussed in innovative tele-ECHO mentoring program on addiction management.

Asian J Psychiatr 2020 Apr 18;52:102060. Epub 2020 Apr 18.

Virtual Knowledge Network ECHO, Centre for Addiction Medicine, NIMHANS Digital Academy, Dept of Psychiatry, National Institute of Mental Health and Neurosciences, Bangalore, 560029, India. Electronic address:

NIMHANS ECHO (Extension for Community Healthcare Outcomes) model uses a video conferencing app to connect multiple community health care teams simultaneously with addiction treatment specialists and builds treatment capacity via mentorship and case-based learning. The aim was to investigate the characteristics of 102 cases discussed by remote community health providers in 28 weekly tele-ECHO addiction clinics between January to July 2019. Among the presented cases, the lifetime and current use of alcohol was 80 % and 71 %, respectively, and that of tobacco was 60 % and 56 %. Read More

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http://dx.doi.org/10.1016/j.ajp.2020.102060DOI Listing

Global injury morbidity and mortality from 1990 to 2017: results from the Global Burden of Disease Study 2017.

Authors:
Spencer L James Chris D Castle Zachary V Dingels Jack T Fox Erin B Hamilton Zichen Liu Nicholas L S Roberts Dillon O Sylte Nathaniel J Henry Kate E LeGrand Ahmed Abdelalim Amir Abdoli Ibrahim Abdollahpour Rizwan Suliankatchi Abdulkader Aidin Abedi Akine Eshete Abosetugn Abdelrahman I Abushouk Oladimeji M Adebayo Marcela Agudelo-Botero Tauseef Ahmad Rushdia Ahmed Muktar Beshir Ahmed Miloud Taki Eddine Aichour Fares Alahdab Genet Melak Alamene Fahad Mashhour Alanezi Animut Alebel Niguse Meles Alema Suliman A Alghnam Samar Al-Hajj Beriwan Abdulqadir Ali Saqib Ali Mahtab Alikhani Cyrus Alinia Vahid Alipour Syed Mohamed Aljunid Amir Almasi-Hashiani Nihad A Almasri Khalid Altirkawi Yasser Sami Abdeldayem Amer Saeed Amini Arianna Maever Loreche Amit Catalina Liliana Andrei Alireza Ansari-Moghaddam Carl Abelardo T Antonio Seth Christopher Yaw Appiah Jalal Arabloo Morteza Arab-Zozani Zohreh Arefi Olatunde Aremu Filippo Ariani Amit Arora Malke Asaad Babak Asghari Nefsu Awoke Beatriz Paulina Ayala Quintanilla Getinet Ayano Martin Amogre Ayanore Samad Azari Ghasem Azarian Alaa Badawi Ashish D Badiye Eleni Bagli Atif Amin Baig Mohan Bairwa Ahad Bakhtiari Arun Balachandran Maciej Banach Srikanta K Banerjee Palash Chandra Banik Amrit Banstola Suzanne Lyn Barker-Collo Till Winfried Bärnighausen Lope H Barrero Akbar Barzegar Mohsen Bayati Bayisa Abdissa Baye Neeraj Bedi Masoud Behzadifar Tariku Tesfaye Bekuma Habte Belete Corina Benjet Derrick A Bennett Isabela M Bensenor Kidanemaryam Berhe Pankaj Bhardwaj Anusha Ganapati Bhat Krittika Bhattacharyya Sadia Bibi Ali Bijani Muhammad Shahdaat Bin Sayeed Guilherme Borges Antonio Maria Borzì Soufiane Boufous Alexandra Brazinova Nikolay Ivanovich Briko Shyam S Budhathoki Josip Car Rosario Cárdenas Félix Carvalho João Mauricio Castaldelli-Maia Carlos A Castañeda-Orjuela Giulio Castelpietra Ferrán Catalá-López Ester Cerin Joht S Chandan Wagaye Fentahun Chanie Soosanna Kumary Chattu Vijay Kumar Chattu Irini Chatziralli Neha Chaudhary Daniel Youngwhan Cho Mohiuddin Ahsanul Kabir Chowdhury Dinh-Toi Chu Samantha M Colquhoun Maria-Magdalena Constantin Vera M Costa Giovanni Damiani Ahmad Daryani Claudio Alberto Dávila-Cervantes Feleke Mekonnen Demeke Asmamaw Bizuneh Demis Gebre Teklemariam Demoz Desalegn Getnet Demsie Afshin Derakhshani Kebede Deribe Rupak Desai Mostafa Dianati Nasab Diana Dias da Silva Zahra Sadat Dibaji Forooshani Kerrie E Doyle Tim Robert Driscoll Eleonora Dubljanin Bereket Duko Adema Arielle Wilder Eagan Aziz Eftekhari Elham Ehsani-Chimeh Maysaa El Sayed Zaki Demelash Abewa Elemineh Shaimaa I El-Jaafary Ziad El-Khatib Christian Lycke Ellingsen Mohammad Hassan Emamian Daniel Adane Endalew Sharareh Eskandarieh Pawan Sirwan Faris Andre Faro Farshad Farzadfar Yousef Fatahi Wubalem Fekadu Tomas Y Ferede Seyed-Mohammad Fereshtehnejad Eduarda Fernandes Pietro Ferrara Garumma Tolu Feyissa Irina Filip Florian Fischer Morenike Oluwatoyin Folayan Masoud Foroutan Joel Msafiri Francis Richard Charles Franklin Takeshi Fukumoto Biniyam Sahiledengle Geberemariyam Abadi Kahsu Gebre Ketema Bizuwork Gebremedhin Gebreamlak Gebremedhn Gebremeskel Berhe Gebremichael Getnet Azeze Gedefaw Birhanu Geta Mansour Ghafourifard Farhad Ghamari Ahmad Ghashghaee Asadollah Gholamian Tiffany K Gill Alessandra C Goulart Ayman Grada Michal Grivna Mohammed Ibrahim Mohialdeen Gubari Rafael Alves Guimarães Yuming Guo Gaurav Gupta Juanita A Haagsma Nima Hafezi-Nejad Hassan Haghparast Bidgoli Brian James Hall Randah R Hamadeh Samer Hamidi Josep Maria Haro Md Mehedi Hasan Amir Hasanzadeh Soheil Hassanipour Hadi Hassankhani Hamid Yimam Hassen Rasmus Havmoeller Khezar Hayat Delia Hendrie Fatemeh Heydarpour Martha Híjar Hung Chak Ho Chi Linh Hoang Michael K Hole Ramesh Holla Naznin Hossain Mehdi Hosseinzadeh Sorin Hostiuc Guoqing Hu Segun Emmanuel Ibitoye Olayinka Stephen Ilesanmi Irena Ilic Milena D Ilic Leeberk Raja Inbaraj Endang Indriasih Seyed Sina Naghibi Irvani Sheikh Mohammed Shariful Islam M Mofizul Islam Rebecca Q Ivers Kathryn H Jacobsen Mohammad Ali Jahani Nader Jahanmehr Mihajlo Jakovljevic Farzad Jalilian Sudha Jayaraman Achala Upendra Jayatilleke Ravi Prakash Jha Yetunde O John-Akinola Jost B Jonas Nitin Joseph Farahnaz Joukar Jacek Jerzy Jozwiak Suresh Banayya Jungari Mikk Jürisson Ali Kabir Rajendra Kadel Amaha Kahsay Leila R Kalankesh Rohollah Kalhor Teshome Abegaz Kamil Tanuj Kanchan Neeti Kapoor Manoochehr Karami Amir Kasaeian Hagazi Gebremedhin Kassaye Taras Kavetskyy Hafte Kahsay Kebede Peter Njenga Keiyoro Abraham Getachew Kelbore Bayew Kelkay Yousef Saleh Khader Morteza Abdullatif Khafaie Nauman Khalid Ibrahim A Khalil Rovshan Khalilov Mohammad Khammarnia Ejaz Ahmad Khan Maseer Khan Tripti Khanna Habibolah Khazaie Fatemeh Khosravi Shadmani Roba Khundkar Daniel N Kiirithio Young-Eun Kim Daniel Kim Yun Jin Kim Adnan Kisa Sezer Kisa Hamidreza Komaki Shivakumar K M Kondlahalli Vladimir Andreevich Korshunov Ai Koyanagi Moritz U G Kraemer Kewal Krishan Burcu Kucuk Bicer Nuworza Kugbey Vivek Kumar Nithin Kumar G Anil Kumar Manasi Kumar Girikumar Kumaresh Om P Kurmi Oluwatosin Kuti Carlo La Vecchia Faris Hasan Lami Prabhat Lamichhane Justin J Lang Van C Lansingh Dennis Odai Laryea Savita Lasrado Arman Latifi Paolo Lauriola Janet L Leasher Shaun Wen Huey Lee Tsegaye Lolaso Lenjebo Miriam Levi Shanshan Li Shai Linn Xuefeng Liu Alan D Lopez Paulo A Lotufo Raimundas Lunevicius Ronan A Lyons Mohammed Madadin Muhammed Magdy Abd El Razek Narayan Bahadur Mahotra Marek Majdan Azeem Majeed Jeadran N Malagon-Rojas Venkatesh Maled Reza Malekzadeh Deborah Carvalho Malta Navid Manafi Amir Manafi Ana-Laura Manda Narayana Manjunatha Fariborz Mansour-Ghanaei Borhan Mansouri Mohammad Ali Mansournia Joemer C Maravilla Lyn M March Amanda J Mason-Jones Seyedeh Zahra Masoumi Benjamin Ballard Massenburg Pallab K Maulik Gebrekiros Gebremichael Meles Addisu Melese Zeleke Aschalew Melketsedik Peter T N Memiah Walter Mendoza Ritesh G Menezes Meresa Berwo Mengesha Melkamu Merid Mengesha Tuomo J Meretoja Atte Meretoja Hayimro Edemealem Merie Tomislav Mestrovic Bartosz Miazgowski Tomasz Miazgowski Ted R Miller G K Mini Andreea Mirica Erkin M Mirrakhimov Mehdi Mirzaei-Alavijeh Prasanna Mithra Babak Moazen Masoud Moghadaszadeh Efat Mohamadi Yousef Mohammad Karzan Abdulmuhsin Mohammad Aso Mohammad Darwesh Naser Mohammad Gholi Mezerji Abdollah Mohammadian-Hafshejani Milad Mohammadoo-Khorasani Reza Mohammadpourhodki Shafiu Mohammed Jemal Abdu Mohammed Farnam Mohebi Mariam Molokhia Lorenzo Monasta Yoshan Moodley Mahmood Moosazadeh Masoud Moradi Ghobad Moradi Maziar Moradi-Lakeh Farhad Moradpour Lidia Morawska Ilais Moreno Velásquez Naho Morisaki Shane Douglas Morrison Tilahun Belete Mossie Atalay Goshu Muluneh Srinivas Murthy Kamarul Imran Musa Ghulam Mustafa Ashraf F Nabhan Ahamarshan Jayaraman Nagarajan Gurudatta Naik Mukhammad David Naimzada Farid Najafi Vinay Nangia Bruno Ramos Nascimento Morteza Naserbakht Vinod Nayak Duduzile Edith Ndwandwe Ionut Negoi Josephine W Ngunjiri Cuong Tat Nguyen Huong Lan Thi Nguyen Rajan Nikbakhsh Dina Nur Anggraini Ningrum Chukwudi A Nnaji Peter S Nyasulu Felix Akpojene Ogbo Onome Bright Oghenetega In-Hwan Oh Emmanuel Wandera Okunga Andrew T Olagunju Tinuke O Olagunju Ahmed Omar Bali Obinna E Onwujekwe Kwaku Oppong Asante Heather M Orpana Erika Ota Nikita Otstavnov Stanislav S Otstavnov Mahesh P A Jagadish Rao Padubidri Smita Pakhale Keyvan Pakshir Songhomitra Panda-Jonas Eun-Kee Park Sangram Kishor Patel Ashish Pathak Sanghamitra Pati George C Patton Kebreab Paulos Amy E Peden Veincent Christian Filipino Pepito Jeevan Pereira Hai Quang Pham Michael R Phillips Marina Pinheiro Roman V Polibin Suzanne Polinder Hossein Poustchi Swayam Prakash Dimas Ria Angga Pribadi Parul Puri Zahiruddin Quazi Syed Mohammad Rabiee Navid Rabiee Amir Radfar Anwar Rafay Ata Rafiee Alireza Rafiei Fakher Rahim Siavash Rahimi Vafa Rahimi-Movaghar Muhammad Aziz Rahman Ali Rajabpour-Sanati Fatemeh Rajati Ivo Rakovac Kavitha Ranganathan Sowmya J Rao Vahid Rashedi Prateek Rastogi Priya Rathi Salman Rawaf Lal Rawal Reza Rawassizadeh Vishnu Renjith Andre M N Renzaho Serge Resnikoff Aziz Rezapour Ana Isabel Ribeiro Jennifer Rickard Carlos Miguel Rios González Luca Ronfani Gholamreza Roshandel Anas M Saad Yogesh Damodar Sabde Siamak Sabour Basema Saddik Saeed Safari Roya Safari-Faramani Hamid Safarpour Mahdi Safdarian S Mohammad Sajadi Payman Salamati Farkhonde Salehi Saleh Salehi Zahabi Marwa R Rashad Salem Hosni Salem Omar Salman Inbal Salz Abdallah M Samy Juan Sanabria Lidia Sanchez Riera Milena M Santric Milicevic Abdur Razzaque Sarker Arash Sarveazad Brijesh Sathian Monika Sawhney Susan M Sawyer Sonia Saxena Mehdi Sayyah David C Schwebel Soraya Seedat Subramanian Senthilkumaran Sadaf G Sepanlou Seyedmojtaba Seyedmousavi Feng Sha Faramarz Shaahmadi Saeed Shahabi Masood Ali Shaikh Mehran Shams-Beyranvand Morteza Shamsizadeh Mahdi Sharif-Alhoseini Hamid Sharifi Aziz Sheikh Mika Shigematsu Jae Il Shin Rahman Shiri Soraya Siabani Inga Dora Sigfusdottir Pankaj Kumar Singh Jasvinder A Singh Dhirendra Narain Sinha Catalin-Gabriel Smarandache Emma U R Smith Amin Soheili Bija Soleymani Ali Reza Soltanian Joan B Soriano Muluken Bekele Sorrie Ireneous N Soyiri Dan J Stein Mark A Stokes Mu'awiyyah Babale Sufiyan Hafiz Ansar Rasul Suleria Bryan L Sykes Rafael Tabarés-Seisdedos Karen M Tabb Biruk Wogayehu Taddele Degena Bahrey Tadesse Animut Tagele Tamiru Ingan Ukur Tarigan Yonatal Mesfin Tefera Arash Tehrani-Banihashemi Merhawi Gebremedhin Tekle Gebretsadkan Hintsa Tekulu Ayenew Kassie Tesema Berhe Etsay Tesfay Rekha Thapar Asres Bedaso Tilahune Kenean Getaneh Tlaye Hamid Reza Tohidinik Roman Topor-Madry Bach Xuan Tran Khanh Bao Tran Jaya Prasad Tripathy Alexander C Tsai Lorainne Tudor Car Saif Ullah Irfan Ullah Maida Umar Bhaskaran Unnikrishnan Era Upadhyay Olalekan A Uthman Pascual R Valdez Tommi Juhani Vasankari Narayanaswamy Venketasubramanian Francesco S Violante Vasily Vlassov Yasir Waheed Girmay Teklay Weldesamuel Andrea Werdecker Taweewat Wiangkham Haileab Fekadu Wolde Dawit Habte Woldeyes Dawit Zewdu Wondafrash Temesgen Gebeyehu Wondmeneh Adam Belay Wondmieneh Ai-Min Wu Rajaram Yadav Ali Yadollahpour Yuichiro Yano Sanni Yaya Vahid Yazdi-Feyzabadi Paul Yip Engida Yisma Naohiro Yonemoto Seok-Jun Yoon Yoosik Youm Mustafa Z Younis Zabihollah Yousefi Yong Yu Chuanhua Yu Hasan Yusefzadeh Telma Zahirian Moghadam Zoubida Zaidi Sojib Bin Zaman Mohammad Zamani Maryam Zamanian Hamed Zandian Ahmad Zarei Fatemeh Zare Zhi-Jiang Zhang Yunquan Zhang Sanjay Zodpey Lalit Dandona Rakhi Dandona Louisa Degenhardt Samath Dhamminda Dharmaratne Simon I Hay Ali H Mokdad Robert C Reiner Benn Sartorius Theo Vos

Inj Prev 2020 Apr 24. Epub 2020 Apr 24.

Institute for Health Metrics and Evaluation, University of Washington, Seattle, WA, USA.

Background: Past research in population health trends has shown that injuries form a substantial burden of population health loss. Regular updates to injury burden assessments are critical. We report Global Burden of Disease (GBD) 2017 Study estimates on morbidity and mortality for all injuries. Read More

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http://dx.doi.org/10.1136/injuryprev-2019-043494DOI Listing
April 2020
1.941 Impact Factor

Personality and Islamic religiosity: Preliminary survey data of Bruneian Malay Muslim university students and their psychological well-being, unethical behavior, and dark triad traits.

Data Brief 2020 Jun 7;30:105486. Epub 2020 Apr 7.

Academy of Brunei Studies, Universiti Brunei Darussalam, Brunei.

The paper presents data collected using measures of personality, Islamic religiosity, psychological well-being, unethical behavior, and dark triad traits. The sample consists 277 Bruneian Malay Muslim university students. The participants were sampled at a public university in Brunei. Read More

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http://dx.doi.org/10.1016/j.dib.2020.105486DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7160428PMC

Classification of pathogens by Raman spectroscopy combined with generative adversarial networks.

Sci Total Environ 2020 Jul 4;726:138477. Epub 2020 Apr 4.

Key Laboratory of Coastal Biology and Biological Resources Utilization, CAS Key Laboratory of Coastal Environmental Processes and Ecological Remediation, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai 264003, P. R. China; National-Regional Joint Engineering Research Center for Soil Pollution Control and Remediation in South China, Guangdong Key Laboratory of Integrated Agro-environmental Pollution Control and Management, Guangdong Institute of Eco-environmental Science & Technology, Guangdong Academy of Sciences, Guangzhou 510650, PR China; Guangdong-Hong Kong-Macao Joint Laboratory for Environmental Pollution and Control, Guangzhou Institute of Geochemistry, Chinese Academy of Sciences, Guangzhou 510640, PR China. Electronic address:

Rapid identification of marine pathogens is very important in marine ecology. Artificial intelligence combined with Raman spectroscopy is a promising choice for identifying marine pathogens due to its rapidity and efficiency. However, considering the cost of sample collection and the challenging nature of the experimental environment, only limited spectra are typically available to build a classification model, which hinders qualitative analysis. Read More

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http://dx.doi.org/10.1016/j.scitotenv.2020.138477DOI Listing

Networked health care: Rethinking value creation in learning health care systems.

Learn Health Syst 2020 Apr 5;4(2):e10212. Epub 2019 Dec 5.

The Dartmouth Institute for Health Policy and Clinical Practice Geisel School of Medicine at Dartmouth Hanover New Hampshire.

Creating better value in health care service today is very challenging. The social pressure to do so is real for every health care system and its leadership. Real benefit has been achieved in manufacturing sector work by the use of "value-chain" thinking, which assumes that the work is a series of linked processes necessary to make a product. Read More

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http://dx.doi.org/10.1002/lrh2.10212DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7156860PMC

Experience-Based Swedish TTO and VAS Value Sets for EQ-5D-5L Health States.

Pharmacoeconomics 2020 Apr 20. Epub 2020 Apr 20.

Center for Medical Technology Assessment, Department of Medical and Health Sciences, Linköping University, Linköping, Sweden.

Background And Objective: Although value sets for the five-level version of the generic health-related quality-of-life instrument EQ-5D are emerging, there is still no value set available in the literature based on time trade-off valuations made by individuals experiencing the valued health states. The aim of this study was to estimate experience-based value sets for the EQ-5D-5L for Sweden using time trade-off and visual analogue scale valuation methods.

Methods: In a large, cross-sectional, population-based, self-administered postal health survey, the EQ-5D-5L descriptive system, EQ visual analogue scale and a time trade-off question were included. Read More

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http://dx.doi.org/10.1007/s40273-020-00905-7DOI Listing

[Analysis on the situation of being supported by the national natural science foundation of China in the field of occupational diseases from 2010 to 2019].

Zhonghua Lao Dong Wei Sheng Zhi Ye Bing Za Zhi 2020 Feb;38(2):125-128

National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention 100050 Beijing, China.

To understand the situation supported by the National Natural Science Foundation in the field of occupational diseases (H2402) in China, so as to provide a reference basis for the application and research of scientific researchers in the field of occupational diseases in China. The information system of scientific and technological achievements was used to search the financial support of the National Natural Science Foundation of China (NSFC) in the field of occupational diseases from 2010 to 2019. From 2010 to 2019, a total of 55 projects were funded under the Occupational Disease code (H2402) , with a total funding of 22. Read More

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http://dx.doi.org/10.3760/cma.j.issn.1001-9391.2020.02.010DOI Listing
February 2020

Fragility fractures in Europe: burden, management and opportunities.

Arch Osteoporos 2020 04 19;15(1):59. Epub 2020 Apr 19.

Mary MacKillop Health Institute, Catholic University of Australia, Melbourne, Australia.

This report provides an overview and a comparison of the burden and management of fragility fractures in the largest five countries of the European Union plus Sweden (EU6). In 2017, new fragility fractures in the EU6 are estimated at 2.7 million with an associated annual cost of €37. Read More

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http://dx.doi.org/10.1007/s11657-020-0706-yDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7166207PMC

Smartphone as a monitoring tool for bipolar disorder: a systematic review including data analysis, machine learning algorithms and predictive modelling.

Int J Med Inform 2020 06 31;138:104131. Epub 2020 Mar 31.

Department of Affective Disorders, Institute of Psychiatry and Neurology, Sobieskiego 9, 02-957 Warsaw, Poland.

Background: Bipolar disorder (BD) is a chronic illness with a high recurrence rate. Smartphones can be a useful tool for detecting prodromal symptoms of episode recurrence (through real-time monitoring) and providing options for early intervention between outpatient visits.

Aims: The aim of this systematic review is to overview and discuss the studies on the smartphone-based systems that monitor or detect the phase change in BD. Read More

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http://dx.doi.org/10.1016/j.ijmedinf.2020.104131DOI Listing

The International Academy of Health Sciences Informatics (IAHSI): IMIAs Academy is Now Established and on Track.

Yearb Med Inform 2020 Apr 17. Epub 2020 Apr 17.

Clinical Informatics Center, University of Texas Southwestern Medical Center, Dallas, USA.

Objectives: To summarize the major activities of the International Academy of Health Sciences Informatics (IAHSI) from 2018 until 2019, and to provide an outline of actions planned for 2020.

Method: Reporting about these activities and actions by the members of the Academy's first Board.

Results: Academy bylaws were accepted by the Academy Plenary and the IMIA General Assembly on August 25th, 2019 and August 26th, 2019, respectively. Read More

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http://dx.doi.org/10.1055/s-0040-1701971DOI Listing

How a Malnutrition Quality Improvement Initiative Furthers Malnutrition Measurement and Care: Results From a Hospital Learning Collaborative.

JPEN J Parenter Enteral Nutr 2020 Apr 13. Epub 2020 Apr 13.

Quality Management, The Academy of Nutrition and Dietetics, Chicago, Illinois, USA.

Background: Malnutrition in hospitalized patients can adversely affect health outcomes and increase the cost of care. Real-world strategies are needed for prompt identification and treatment of patients at risk of malnutrition.

Objectives: The aim of this quality improvement (QI) study was to measure the impact of a nutrition-focused program on the malnutrition care processes of participating hospitals. Read More

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http://dx.doi.org/10.1002/jpen.1833DOI Listing

A congruence perspective on how human and social capital affect learning capability and innovation.

PLoS One 2020 13;15(4):e0231504. Epub 2020 Apr 13.

Central University of Finance and Economics, Beijing, China.

Human capital and social capital are vital for sustainable development of organization, but existing studies are inadequate to explore the synergistic effect of them on organizational behaviors or organizational outcomes. The research employed multiple-source questionnaire to collect data of more than 400 R&D firms from leaders and corresponding employees in Chinese context. Bootstrapping method and response surface were used to analyze the associations between all the parameters. Read More

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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0231504PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7153854PMC

A study on giant panda recognition based on images of a large proportion of captive pandas.

Ecol Evol 2020 Apr 10;10(7):3561-3573. Epub 2020 Mar 10.

Chengdu Research Base of Giant Panda Breeding Chengdu China.

As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. Read More

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http://dx.doi.org/10.1002/ece3.6152DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7141006PMC

Leader Academy: A layered approach to learning leadership.

Curr Pharm Teach Learn 2020 Mar 11;12(3):326-330. Epub 2019 Dec 11.

Clinical Pharmacy and Outcome Sciences, Medical University of South Carolina College of Pharmacy, Charleston, SC 29425, United States.

Background And Purpose: Leader Academy (LA) is a co-curricular experience for students that builds communication skills, fosters leadership skills, and offers opportunities in professional development. The program couples leadership development during the first year of the curriculum with activities conducted in a team-based learning course.

Educational Activity And Setting: An emotional intelligence (EI) assessment was administered to students during their first year. Read More

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http://dx.doi.org/10.1016/j.cptl.2019.12.012DOI Listing

Gut microbiota in children with juvenile idiopathic arthritis: characteristics, biomarker identification, and usefulness in clinical prediction.

BMC Genomics 2020 Apr 7;21(1):286. Epub 2020 Apr 7.

Department of Rheumatology Immunology and Allergy, Children's Hospital, Zhejiang University School of Medicine, Hangzhou, Zhejiang Province, China.

Background: Recent studies have suggested that the gut microbiota is altered in children with juvenile idiopathic arthritis (JIA). However, age, sex, and body mass index (BMI) were not matched in the previous studies, and the results are inconsistent. We conducted an age-, sex-, and BMI-matched cross-sectional study to characterize the gut microbiota in children with JIA, and evaluate its potential in clinical prediction. Read More

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http://dx.doi.org/10.1186/s12864-020-6703-0DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7137182PMC

Groundwater Potential Mapping Combining Artificial Neural Network and Real AdaBoost Ensemble Technique: The DakNong Province Case-study, Vietnam.

Int J Environ Res Public Health 2020 04 4;17(7). Epub 2020 Apr 4.

University of Transport Technology, Hanoi 100000, Vietnam.

The main aim of this study is to assess groundwater potential of the DakNong province, Vietnam, using an advanced ensemble machine learning model (RABANN) that integrates Artificial Neural Networks (ANN) with RealAdaBoost (RAB) ensemble technique. For this study, twelve conditioning factors and wells yield data was used to create the training and testing datasets for the development and validation of the ensemble RABANN model. Area Under the Receiver Operating Characteristic (ROC) curve (AUC) and several statistical performance measures were used to validate and compare performance of the ensemble RABANN model with the single ANN model. Read More

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http://dx.doi.org/10.3390/ijerph17072473DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7177275PMC