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Detecting stranded macro-litter categories on drone orthophoto by a multi-class Neural Network.

Mar Pollut Bull 2021 Jun 9;169:112594. Epub 2021 Jun 9.

INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal. Electronic address:

The use of Unmanned Aerial Systems (UAS, aka drones) images for mapping macro-litter in the environment have been exponentially increasing in the recent years. In this work, we developed a multi-class Neural Network (NN) to automatically identify stranded plastic litter categories on an UAS-derived orthophoto. The best results were assessed for items that did not have substantial intra-class colour variability, such as octopus pots and fishing ropes (F-score = 61%, on average). Read More

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Digital health, big data and smart technologies for the care of patients with systemic autoimmune diseases: Where do we stand?

Autoimmun Rev 2021 Jun 9:102864. Epub 2021 Jun 9.

Department of neuroradiology, A. Rothshield Foundation Hospital, Paris, France. Electronic address:

The past decade has seen tremendous development in digital health, including in innovative new technologies such as Electronic Health Records, telemedicine, virtual visits, wearable technology and sophisticated analytical tools such as artificial intelligence (AI) and machine learning for the deep-integration of big data. In the field of rare connective tissue diseases (rCTDs), these opportunities include increased access to scarce and remote expertise, improved patient monitoring, increased participation and therapeutic adherence, better patient outcomes and patient empowerment. In this review, we discuss opportunities and key-barriers to improve application of digital health technologies in the field of autoimmune diseases. Read More

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Predoctoral substance use disorders curricula: A survey analysis and experiential pedagogy.

J Dent Educ 2021 Jun 11. Epub 2021 Jun 11.

New York State Psychiatric Institute, Columbia University, New York, New York.

Substance Use Disorders (SUD) are chronic health conditions with heritability characteristics, environmental influences, long-term management considerations and they cooccur. The US opioid epidemic is a crisis of both prescription and nonprescription opioid use. Clinicians now have access to evidence-based practices but the evolving trends require continuous attention including curriculum initiatives for dental schools. Read More

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Adapting the listening time for micro-electrode recordings in deep brain stimulation interventions.

Int J Comput Assist Radiol Surg 2021 Jun 11. Epub 2021 Jun 11.

Laboratoire Traitement du Signal et de l'Image (LTSI - INSERM UMR 1099), Université de Rennes 1, Rennes, France.

Purpose: Deep brain stimulation (DBS) is a common treatment for a variety of neurological disorders which involves the precise placement of electrodes at particular subcortical locations such as the subthalamic nucleus. This placement is often guided by auditory analysis of micro-electrode recordings (MERs) which informs the clinical team as to the anatomic region in which the electrode is currently positioned. Recent automation attempts have lacked flexibility in terms of the amount of signal recorded, not allowing them to collect more signal when higher certainty is needed or less when the anatomy is unambiguous. Read More

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Future of biomarker evaluation in the realm of artificial intelligence algorithms: application in improved therapeutic stratification of patients with breast and prostate cancer.

J Clin Pathol 2021 Jun 11. Epub 2021 Jun 11.

School of Biomolecular and Biomedical Science, Conway Institute, University College Dublin, Dublin, Ireland.

Clinical workflows in oncology depend on predictive and prognostic biomarkers. However, the growing number of complex biomarkers contributes to costly and delayed decision-making in routine oncology care and treatment. As cancer is expected to rank as the leading cause of death and the single most important barrier to increasing life expectancy in the 21st century, there is a major emphasis on precision medicine, particularly individualisation of treatment through better prediction of patient outcome. Read More

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Applications of machine learning in the chemical pathology laboratory.

J Clin Pathol 2021 Jun 11. Epub 2021 Jun 11.

Computer Science, University of Pretoria Faculty of Engineering Built Environment and IT, Pretoria, Gauteng, South Africa.

Machine learning (ML) is an area of artificial intelligence that provides computer programmes with the capacity to autodidact and learn new skills from experience, without continued human programming. ML algorithms can analyse large data sets quickly and accurately, by supervised and unsupervised learning techniques, to provide classification and prediction value outputs. The application of ML to chemical pathology can potentially enhance efficiency at all phases of the laboratory's total testing process. Read More

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Development of a predictive risk model for all-cause mortality in patients with diabetes in Hong Kong.

BMJ Open Diabetes Res Care 2021 Jun;9(1)

Cardiovascular Analytics Group, Laboratory of Cardiovascular Physiology, Hong Kong

Introduction: Patients with diabetes mellitus are risk of premature death. In this study, we developed a machine learning-driven predictive risk model for all-cause mortality among patients with type 2 diabetes mellitus using multiparametric approach with data from different domains.

Research Design And Methods: This study used territory-wide data of patients with type 2 diabetes attending public hospitals or their associated ambulatory/outpatient facilities in Hong Kong between January 1, 2009 and December 31, 2009. Read More

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Promoting social emotional development during the paediatric well-child visit: a demonstration project.

BMJ Open Qual 2021 Jun;10(2)

Programs, National Institute for Children's Health Quality (NICHQ), Boston, Massachusetts, USA.

Supporting social emotional development, beginning at birth, can improve lifelong health. The American Academy of Paediatrics recommends 12 well-child visits between birth and age 3 years. Each well-child visit provides a unique opportunity to interact with and support families to promote social emotional development of children. Read More

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Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction.

Mayo Clin Proc 2021 Jun 8. Epub 2021 Jun 8.

Department of Cardiovascular Medicine, Mayo Clinic, Rochester, MN.

Objective: To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65.

Patients And Methods: We used decision analytic modeling to perform a cost-effectiveness analysis of the use of AI-ECG to screen for asymptomatic left ventricular dysfunction (ALVD) once at age 65 compared with no screening. This screening consisted of an initial screening decision tree and subsequent construction of a Markov model. Read More

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Ensemble machine learning approach for screening of coronary heart disease based on echocardiography and risk factors.

BMC Med Inform Decis Mak 2021 Jun 11;21(1):187. Epub 2021 Jun 11.

Department of Cardiology, Beijing Hospital, National Center of Gerontology; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, Beijing, China.

Background: Extensive clinical evidence suggests that a preventive screening of coronary heart disease (CHD) at an earlier stage can greatly reduce the mortality rate. We use 64 two-dimensional speckle tracking echocardiography (2D-STE) features and seven clinical features to predict whether one has CHD.

Methods: We develop a machine learning approach that integrates a number of popular classification methods together by model stacking, and generalize the traditional stacking method to a two-step stacking method to improve the diagnostic performance. Read More

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COVID-19 pandemic in Africa: Is it time for water, sanitation and hygiene to climb up the ladder of global priorities?

Sci Total Environ 2021 Jun 3;791:148252. Epub 2021 Jun 3.

Universidad de Granada, Campus de Cartuja, s/n, 18071 Granada, Spain.

In the current pandemic context, it is necessary to remember the lessons learned from previous outbreaks in Africa, where the incidence of other diseases could rise if most resources are directed to tackle the emergency. Improving the access to water, sanitation and hygiene (WASH) could be a win-win strategy, because the lack of these services not only hampers the implementation of preventive measures against SARS-CoV-2 (e.g. Read More

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Prediction of false positive SARS-CoV-2 molecular results in a high-throughput open platform system.

J Mol Diagn 2021 Jun 8. Epub 2021 Jun 8.

Department of Laboratory Medicine & Pathology, Division of Molecular Pathology and Genomics, University of Minnesota, Minneapolis, MN, USA. Electronic address:

Widespread high-throughput testing for identification of SARS-CoV-2 infection by RT-PCR has been a foundation in the response to the COVID-19 pandemic. Quality assurance metrics for these RT-PCR tests are still evolving as testing becomes widely implemented. As testing increases, it is important to understand performance characteristics and the errors associated with these tests. Read More

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Effectiveness of Supplementary Materials in Teaching the Veterinary Neurologic Examination.

J Vet Med Educ 2021 Jun 11:e20210014. Epub 2021 Jun 11.

Clinical neurology can be difficult for veterinary students to comprehend, and part of understanding the clinical aspect is performing a proper neurologic examination. In this study, first-year veterinary students in a Small Animal Physical Exam and Anatomy rotation were given supplemental learning activities to determine their effect on student procedural knowledge and motivation in performing a neurologic examination. Students were randomly assigned to one of three groups: the first watched a video of a clinician performing the neurologic examination, the second read a handout about the neurologic exam, and the third was the control group, where students were not provided any supplemental activities. Read More

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The active feedback program: bringing medical students out of the shadows.

Med Educ Online 2021 Dec;26(1):1939842

Department of Neurology, Georgetown University, Washington, DC, USA.

Despite many advances in medical education, medical students continue to mostly shadow on inpatient rotations like Neurology. They seldom receive face-to-face feedback or mentorship from attending physicians. This results from not training attending physicians how to integrate medical students into clinical activities in a way that does not detract from patient rounds. Read More

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December 2021

Assessing people with dementia participating in cognitive stimulation activities-A qualitative pilot video analysis exploring the importance of facilitating the participation.

Health Expect 2021 Jun 11. Epub 2021 Jun 11.

University of Northampton, Northampton, UK.

Background: This pilot video analysis was part of a feasibility control study, which aimed to gain information about the size and variability of the changes in outcome measures to plan a substantive effect study. It compared a cognitive stimulation programme named Lifelong Learning with other existing dementia services.

Objective: The pilot video analysis explored how facilitation is performed, when assessing people with dementia with standardized measures, to ensure their participation in research. Read More

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Estimating heterogeneous survival treatment effect in observational data using machine learning.

Stat Med 2021 Jun 10. Epub 2021 Jun 10.

Department of Biostatistics, Yale University School of Public Health, New Haven, Connecticut, USA.

Methods for estimating heterogeneous treatment effect in observational data have largely focused on continuous or binary outcomes, and have been relatively less vetted with survival outcomes. Using flexible machine learning methods in the counterfactual framework is a promising approach to address challenges due to complex individual characteristics, to which treatments need to be tailored. To evaluate the operating characteristics of recent survival machine learning methods for the estimation of treatment effect heterogeneity and inform better practice, we carry out a comprehensive simulation study presenting a wide range of settings describing confounded heterogeneous survival treatment effects and varying degrees of covariate overlap. Read More

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Assessing knowledge, attitudes, and practices towards causal directed acyclic graphs: a qualitative research project.

Eur J Epidemiol 2021 Jun 10. Epub 2021 Jun 10.

Department of Epidemiology, Boston University School of Public Health, Boston, MA, 02118, USA.

Causal graphs provide a key tool for optimizing the validity of causal effect estimates. Although a large literature exists on the mathematical theory underlying the use of causal graphs, less literature exists to aid applied researchers in understanding how best to develop and use causal graphs in their research projects. We sought to understand why researchers do or do not regularly use DAGs by surveying practicing epidemiologists and medical researchers on their knowledge, level of interest, attitudes, and practices towards the use of causal graphs in applied epidemiology and health research. Read More

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Clinical evaluation of a phantom-based deep convolutional neural network for whole-body-low-dose and ultra-low-dose CT skeletal surveys.

Skeletal Radiol 2021 Jun 10. Epub 2021 Jun 10.

Department of Radiology, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.

Objective: This study evaluated the clinical utility of a phantom-based convolutional neural network noise reduction framework for whole-body-low-dose CT skeletal surveys.

Materials And Methods: The CT exams of ten patients with multiple myeloma were retrospectively analyzed. Exams were acquired with routine whole-body-low-dose CT protocol and projection noise insertion was used to simulate 25% dose exams. Read More

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T-staging pulmonary oncology from radiological reports using natural language processing: translating into a multi-language setting.

Insights Imaging 2021 Jun 10;12(1):77. Epub 2021 Jun 10.

Department of Radiation Oncology (MAASTRO), GROW School for Oncology and Developmental Biology, Maastricht University Medical Center, Maastricht, The Netherlands.

Background: In the era of datafication, it is important that medical data are accurate and structured for multiple applications. Especially data for oncological staging need to be accurate to stage and treat a patient, as well as population-level surveillance and outcome assessment. To support data extraction from free-text radiological reports, Dutch natural language processing (NLP) algorithm was built to quantify T-stage of pulmonary tumors according to the tumor node metastasis (TNM) classification. Read More

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Students' perceptions of FSBio 201, a CURE-based course that scaffolds research and scientific communication, align with learning outcomes.

Integr Comp Biol 2021 Jun 10. Epub 2021 Jun 10.

Dept. of Biology, Allegheny College. 520 N. Main St., Meadville, PA 16335.

Incorporating active research opportunities into undergraduate curricula is one of the most cited elements demonstrated to improve inclusive excellence and retention in all STEM fields. Allegheny College has a long and nationally-recognized tradition of collaborative student-faculty research within the academic curriculum and as co-curricular opportunities. We present an example of the former, a Course-based Undergraduate Research Experience (CURE), FSBio 201, that has been central to Allegheny's biology curriculum for over two decades. Read More

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Nursing Students' and Preceptors' Experiences with Using an Assessment Tool for Feedback and Reflection in Supervision of Clinical Skills: A Qualitative Pilot Study.

Nurs Res Pract 2021 18;2021:5551662. Epub 2021 May 18.

Faculty of Health and Social Sciences, Department of Nursing and Health Sciences, University of South-East Norway, PoBox 7053, N-3007 Drammen, Norway.

Background: There is a need to improve students' learning in clinical practice. Undergraduate students need guidance when it comes to transferring knowledge from the classroom to clinical practice in community health services. Competence Development of Practical Procedures (COPPs), a simulation assessment tool, was used to explore students' and preceptors' experiences with feedback and reflection during the supervision of clinical skills in real practice. Read More

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Cric searchable image database as a public platform for conventional pap smear cytology data.

Sci Data 2021 06 10;8(1):151. Epub 2021 Jun 10.

Computing Department, Federal University of Ouro Preto, Ouro Preto, MG, Brazil.

Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates for subsequent treatment. However, one of the main challenges is the accuracy of the conventional method, often subject to high rates of false negative. Read More

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Hybrid AI-assistive diagnostic model permits rapid TBS classification of cervical liquid-based thin-layer cell smears.

Nat Commun 2021 06 10;12(1):3541. Epub 2021 Jun 10.

Department of Pathology, Guangdong Provincial Women's and Children's Dispensary, Shenzhen, Guangdong Province, PR China.

Technical advancements significantly improve earlier diagnosis of cervical cancer, but accurate diagnosis is still difficult due to various factors. We develop an artificial intelligence assistive diagnostic solution, AIATBS, to improve cervical liquid-based thin-layer cell smear diagnosis according to clinical TBS criteria. We train AIATBS with >81,000 retrospective samples. Read More

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A new molecular classification to drive precision treatment strategies in primary Sjögren's syndrome.

Nat Commun 2021 06 10;12(1):3523. Epub 2021 Jun 10.

Institut de Recherches Internationales Servier, Departments of Translational Medicine and Immuno-Inflammatory Diseases Research and Development, Suresnes, France.

There is currently no approved treatment for primary Sjögren's syndrome, a disease that primarily affects adult women. The difficulty in developing effective therapies is -in part- because of the heterogeneity in the clinical manifestation and pathophysiology of the disease. Finding common molecular signatures among patient subgroups could improve our understanding of disease etiology, and facilitate the development of targeted therapeutics. Read More

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Using large-scale experiments and machine learning to discover theories of human decision-making.

Science 2021 06;372(6547):1209-1214

Department of Computer Science, Princeton University, Princeton, NJ 08540, USA.

Predicting and understanding how people make decisions has been a long-standing goal in many fields, with quantitative models of human decision-making informing research in both the social sciences and engineering. We show how progress toward this goal can be accelerated by using large datasets to power machine-learning algorithms that are constrained to produce interpretable psychological theories. Conducting the largest experiment on risky choice to date and analyzing the results using gradient-based optimization of differentiable decision theories implemented through artificial neural networks, we were able to recapitulate historical discoveries, establish that there is room to improve on existing theories, and discover a new, more accurate model of human decision-making in a form that preserves the insights from centuries of research. Read More

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Behavioral Therapy for Tremor or Dystonia Affecting Voice in Speakers with Hyperkinetic Dysarthria: A Systematic Review.

J Voice 2021 Jun 7. Epub 2021 Jun 7.

Department of Physical Medicine & Rehabilitation, Feinberg School of Medicine, Northwestern University, Chicago, Illinois; Think + Speak Lab, Shirley Ryan AbilityLab, Chicago, Illinois.

Introduction: Hyperkinetic dysarthria is characterized by atypical involuntary movements within the speech mechanism that may affect the respiratory, laryngeal, pharyngeal-oral, or velopharyngeal-nasal subsystems and may alter speech production. Although articulatory impairments are commonly considered in hyperkinetic dysarthria, speakers with hyperkinetic dysarthria may also present with changes in voice quality, pitch, and loudness. In approximately 70% of speakers with hyperkinetic dysarthria, these voice alterations are associated with tremor or dystonia. Read More

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Medical recommender systems based on continuous-valued logic and multi-criteria decision operators, using interpretable neural networks.

BMC Med Inform Decis Mak 2021 Jun 11;21(1):186. Epub 2021 Jun 11.

Knowledgepark GmbH, Leonrodstr. 68, 80636, Munich, Germany.

Background: Out of the pressure of Digital Transformation, the major industrial domains are using advanced and efficient digital technologies to implement processes that are applied on a daily basis. Unfortunately, this still does not happen in the same way in the medical domain. For this reason, doctors usually do not have the time or knowledge to evaluate all alternative treatment options for each patient accurately and individually. Read More

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A picture is worth a thousand words: a history of diagnostic imaging for lymphoma.

Br J Radiol 2021 Jun 11:20210285. Epub 2021 Jun 11.

Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, USA.

The journey from early drawings of Thomas Hodgkin's patients to deep learning with radiomics in lymphoma has taken nearly 200 years, and in many ways, it parallels the journey of medicine. By tracing the history of imaging in clinical lymphoma practice, we can better understand the motivations for current imaging practices. The earliest imaging modalities of the 2D era, each had varied, site-dependent sensitivity and the accuracy of imaging studies allowing new diagnostic and therapeutic techniques. Read More

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Using machine learning to improve the discriminative power of the FERD screener in classifying patients with schizophrenia and healthy adults.

J Affect Disord 2021 Jun 1;292:102-107. Epub 2021 Jun 1.

School of Occupational Therapy, College of Medicine, National Taiwan University, Taipei, Taiwan;; Department of Physical Medicine and Rehabilitation, National Taiwan University Hospital, Taipei, Taiwan;; Department of Occupational Therapy, College of Medical and Health Science, Asia University, Taichung, Taiwan.. Electronic address:

Background Facial emotion recognition deficit (FERD) seems to be an obvious feature of patients with schizophrenia and has great potential for classifying patients and non-patients. The FERD screener was previously developed to classify patients from healthy adults. However, an obvious drawback of this screener is that the recommended cut-off scores could enhance either sensitivity or specificity (about 0. Read More

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Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Comput Biol Med 2021 Jun 3;134:104521. Epub 2021 Jun 3.

eResearch Centre, James Cook University, Townsville, Queensland, 4811, Australia.

Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premature babies cared for in neonatal intensive care units (NICUs). Mortality risk prediction in this setting can greatly improve patient outcomes and resource utilization. However, existing schemes often require laborious medical testing and calculation, and are typically only calculated once at admission. Read More

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