280,256 results match your criteria methods proposed

Development and Validation of a Machine-Learning-Based Decision Support Tool for Residency Applicant Screening and Review.

Acad Med 2021 Aug 3. Epub 2021 Aug 3.

J. Burk-Rafel is assistant professor of medicine and assistant director of UME-GME innovation, Institute for Innovations in Medical Education, NYU Grossman School of Medicine, New York, New York. At the time this work was completed, he was an internal medicine resident at NYU Langone Health, New York, New York; ORCID: https://orcid.org/0000-0003-3785-2154. I. Reinstein is a research scientist, Institute for Innovations in Medical Education, NYU Grossman School of Medicine, New York, New York. J. Feng is an orthopedic surgery resident, Beaumont Health, Royal Oak, Michigan. At the time this work was completed, he was a master's student in biomedical informatics, NYU Grossman School of Medicine Vilcek Institute of Graduate Biomedical Sciences, New York, New York. M.B. Kim is a biostatistician at Aprogen, Seongnam, Republic of Korea. At the time this work was completed, he was a master's student in biomedical informatics, NYU Grossman School of Medicine Vilcek Institute of Graduate Biomedical Sciences, New York, New York. L.H. Miller is assistant professor of cardiology and assistant dean for career advisement, Zucker School of Medicine at Hofstra/Northwell, New York, New York. P.M. Cocks is the Abraham Sunshine Assistant Professor of Medicine, and program director of the internal medicine residency program, NYU Langone Health, New York, New York. M. Marin is director of the division of educational analytics, Institute for Innovations in Medical Education, NYU Grossman School of Medicine, New York, New York. Y. Aphinyanaphongs is director of operational data science and machine learning, NYU Langone Health, New York, New York.

Purpose: Residency programs face overwhelming numbers of residency applications, limiting holistic review. Artificial intelligence techniques have been proposed to address this challenge but have not been created. Here, a multidisciplinary team sought to develop and validate a machine-learning (ML) based decision support tool (DST) for residency applicant screening and review. Read More

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Coronavirus Disease Analysis using Chest X-ray Images and a Novel Deep Convolutional Neural Network.

Photodiagnosis Photodyn Ther 2021 Aug 1:102473. Epub 2021 Aug 1.

Pattern Recognition Lab, Department of Computer & Information Sciences, Pakistan Institute of Engineering & Applied Sciences, Nilore, Islamabad 45650, Pakistan; PIEAS Artificial Intelligence Center (PAIC), Pakistan Institute of Engineering & Applied Sciences, Nilore, Islamabad 45650, Pakistan; Center for Mathematical Sciences, Pakistan Institute of Engineering & & Applied Sciences, Nilore, Islamabad 45650, Pakistan. Electronic address:

Background: The recent emergence of a highly infectious and contagious respiratory viral disease known as COVID-19 has vastly impacted human lives and overloaded the health care system. Therefore, it is crucial to develop a fast and accurate diagnostic system for the timely identification of COVID-19 infected patients and thus to control its spread.

Methods: This work proposes a new deep CNN based technique for COVID-19 classification in X-ray images. Read More

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Highly Dispersed NiGa Catalyst and LaO Promoter Supported by LDO Nanosheets for Dry Reforming of Methane: Synergetic Catalysis by Ni, Ga, and LaO.

Langmuir 2021 Aug 4. Epub 2021 Aug 4.

Shanghai Key Laboratory of Green Chemistry and Chemical Processes. School of Chemistry and Molecular Engineering, East China Normal University, Shanghai 200062, China.

A highly active and stable Ni-based catalyst is the focal point for research on dry reforming of methane (DRM). Here, NiGa/LaO-LDO catalysts composed of highly dispersed NiGa and LaO nanoparticles supported by the MgO/AlO layered double oxide (LDO) nanosheets were synthesized by chemical methods. According to transmission electron microscopy (TEM), energy-dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), CO-TPD, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), and thermal gravitational analysis (TGA), a synergistic reaction mechanism was proposed to explain the superior performance of the NiGa/LaO-LDO catalyst. Read More

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Evolution of Deep Learning Algorithms for MRI-Based Brain Tumor Image Segmentation.

Crit Rev Biomed Eng 2021 ;49(1):77-94

Department of Electronics and Communication Engineering, Delhi Technological University.

Brain tumor textures are among the most challenging features for neuroradiologists to extract from magnetic resonance images (MRIs). Exceptionally high-grade tumors such as gliomas require quick and precise diagnosis and medical intervention due to their infiltrative and fast-spreading nature. Therefore, they require computer assistance instead of manual methods. Read More

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January 2021

The unbiased estimation of the fraction of variance explained by a model.

PLoS Comput Biol 2021 Aug 4;17(8):e1009212. Epub 2021 Aug 4.

Department of Biological Structure, University of Washington, Seattle, Washington, United States of America.

The correlation coefficient squared, r2, is commonly used to validate quantitative models on neural data, yet it is biased by trial-to-trial variability: as trial-to-trial variability increases, measured correlation to a model's predictions decreases. As a result, models that perfectly explain neural tuning can appear to perform poorly. Many solutions to this problem have been proposed, but no consensus has been reached on which is the least biased estimator. Read More

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Intensity of bone involvement: a quantitative 18F-FDG PET/CT evaluation for monitoring outcome of multiple myeloma.

Nucl Med Commun 2021 Aug 3. Epub 2021 Aug 3.

"Gleb Wataghin" Institute of Physics Division of Nuclear Medicine, School of Medical Sciences Center of Hematology and Hemotherapy Department of Pathology, School of Medical Sciences Department of Internal Medicine, University of Campinas (UNICAMP), Campinas, Brazil.

Purpose: The parameter intensity of bone involvement (IBI) was recently proposed to quantitatively assess patients with multiple myeloma using 18F-fluorodeoxyglucose-PET combined with computed tomography (18F-FDG PET/CT) images. Here, we aimed to calculate IBI variation (ΔIBI) between two consecutive PET/CT of the same patient and verified its relationship with a subjective visual analysis of the images and with clinical outcome.

Methods: Consecutive whole-body 18F-FDG PET/CT performed to assess the outcomes of 29 patients diagnosed with multiple myeloma were retrospectively evaluated. Read More

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Measuring Weak Consistency and Weak Transitivity of Pairwise Comparison Matrices.

IEEE Trans Cybern 2021 Aug 4;PP. Epub 2021 Aug 4.

Under the assumption of rational economics, the opinions of decision makers should exhibit some transitivity properties. It is an important issue on how to measure the transitivity properties of the provided preference relations over a set of alternatives. In this study, we report the methods for measuring weak consistency (w-consistency) and weak transitivity (w-transitivity) of pairwise comparison matrices (PCMs) originating from the analytic hierarchy process (AHP). Read More

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Learning from Highly Confident Samples for Automatic Knee Osteoarthritis Severity Assessment: Data from the Osteoarthritis Initiative.

IEEE J Biomed Health Inform 2021 Aug 4;PP. Epub 2021 Aug 4.

Knee osteoarthritis (OA) is a chronic disease that considerably reduces patients' life quality. Preventive therapies require early detection and lifetime monitor of OA progression. In the clinical environment, the severity of OA is classified by Kellgren and Lawrence (KL) grading system, ranging from KL-0 to KL-4. Read More

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Medical Instrument Segmentation in 3D US by Hybrid Constrained Semi-Supervised Learning.

IEEE J Biomed Health Inform 2021 Aug 4;PP. Epub 2021 Aug 4.

Medical instrument segmentation in 3D ultrasound is essential for image-guided intervention. However, to train a successful deep neural network for instrument segmentation, a large number of labeled images are required, which is expensive and time-consuming to obtain. In this article, we propose a semi-supervised learning (SSL) framework for instrument segmentation in 3D US, which requires much less annotation effort than the existing methods. Read More

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Unsupervised Estimation of Monocular Depth and VO in Dynamic Environments via Hybrid Masks.

IEEE Trans Neural Netw Learn Syst 2021 Aug 4;PP. Epub 2021 Aug 4.

Deep learning-based methods have achieved remarkable performance in 3-D sensing since they perceive environments in a biologically inspired manner. Nevertheless, the existing approaches trained by monocular sequences are still prone to fail in dynamic environments. In this work, we mitigate the negative influence of dynamic environments on the joint estimation of depth and visual odometry (VO) through hybrid masks. Read More

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DeepCPPred: a deep learning framework for the discrimination of cell-penetrating peptides and their uptake efficiencies.

IEEE/ACM Trans Comput Biol Bioinform 2021 Aug 4;PP. Epub 2021 Aug 4.

Cell-penetrating peptides (CPPs) are special kind of peptides capable of carrying variety of bioactive molecules such as genetic materials, short interfering RNA and nanoparticles into cell. In recent era, research on CPP has gained substantial interest from researchers to analyze its biological mechanisms for safe drug delivery agents and therapeutic application. Identifying CPP through traditional methods is extremely slow, overpriced and laborious, particularly due to large volume of unannotated peptide sequences accumulating in World Bank repository. Read More

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Essential Protein Recognition via Community Significance.

IEEE/ACM Trans Comput Biol Bioinform 2021 Aug 4;PP. Epub 2021 Aug 4.

Essential protein plays a vital role in understanding the cellular life. With the advance in high-throughput technologies, a number of protein-protein interaction (PPI) networks have been constructed such that essential proteins can be identified from a system biology perspective. Although a series of network-based essential protein discovery methods have been proposed, these existing methods still have some drawbacks. Read More

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Resolution-aware Knowledge Distillation for Efficient Inference.

IEEE Trans Image Process 2021 Aug 4;PP. Epub 2021 Aug 4.

Minimizing the computation complexity is essential for the popularization of deep networks in practical applications. Nowadays, most researches attempt to accelerate deep networks by designing new network structure or compressing the network parameters. Meanwhile, transfer learning techniques such as knowledge distillation are utilized to keep the performance of deep models. Read More

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Learning Brain Functional Networks with Latent Temporal Dependency for MCI Identification.

IEEE Trans Biomed Eng 2021 Aug 4;PP. Epub 2021 Aug 4.

AbstractResting-state functional magnetic resonance imaging (rs-fMRI) has become a popular non-invasive way of diagnosing neurological disorders or their early stages by probing functional connectivity between different brain regions of interest (ROIs) across subjects. In the past decades, researchers have proposed many methods to estimate brain functional networks (BFNs) based on blood-oxygen-level-dependent (BOLD) signals captured by rs-fMRI. However, most of the existing methods estimate BFNs under the assumption that signals are independently sampled, which ignores the temporal dependency and sequential order of different time points (or volumes). Read More

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Channel Characterization of Magnetic Human Body Communication.

IEEE Trans Biomed Eng 2021 Aug 4;PP. Epub 2021 Aug 4.

Objective: The objective of this paper is to model and experimentally validate the path loss benefits of magnetic human body communication (mHBC) using small form-factor-accurate coils operating under realistic conditions.

Methods: A radiating near-field coupling model and numerical simulations are presented to show that the magnetic-dominant near-field coupling between resonant coils offers low path loss across the body and exhibits extra robustness to antenna misalignment compared to far-field RF schemes. To overcome the pitfalls in conventional vector-network-analyzer-based measurement configurations, we propose a standardized setup applied to broadband channel loss measurement with portable instruments. Read More

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Enhancing Recruitment and Retention of Minority Populations for Clinical Research in Pulmonary, Critical Care, and Sleep Medicine: An Official American Thoracic Society Research Statement.

Am J Respir Crit Care Med 2021 Aug;204(3):e26-e50

Well-designed clinical research needs to obtain information that is applicable to the general population. However, most current studies fail to include substantial cohorts of racial/ethnic minority populations. Such underrepresentation may lead to delayed diagnosis or misdiagnosis of disease, wide application of approved interventions without appropriate knowledge of their usefulness in certain populations, and development of recommendations that are not broadly applicable. Read More

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Gaze-angle dependency of pupil-size measurements in head-mounted eye tracking.

Behav Res Methods 2021 Aug 4. Epub 2021 Aug 4.

Pupil Labs, Sanderstraße 28, 12047, Berlin, Germany.

Pupillometry - the study of temporal changes in pupil diameter as a function of external light stimuli or cognitive processing - requires the accurate and gaze-angle independent measurement of pupil dilation. Expected response amplitudes often are only a few percent relative to a pre-stimulus baseline, thus demanding for sub-millimeter accuracy. Video-based approaches to pupil-size measurement aim at inferring pupil dilation from eye images alone. Read More

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Generative image transformer (GIT): unsupervised continuous image generative and transformable model for [I]FP-CIT SPECT images.

Ann Nucl Med 2021 Aug 4. Epub 2021 Aug 4.

Human Health Sciences, Graduate School of Medicine, Kyoto University, 53 Shogoin-Kawaharacho, Sakyo-ku, Kyoto City, Kyoto, Japan.

Objective: Recently, generative adversarial networks began to be actively studied in the field of medical imaging. These models are used for augmenting the variation of images to improve the accuracy of computer-aided diagnosis. In this paper, we propose an alternative new image generative model based on transformer decoder blocks and verify the performance of our model in generating SPECT images that have characteristics of Parkinson's disease patients. Read More

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Comparison of multimodal findings on epileptogenic side in temporal lobe epilepsy using self-organizing maps.

MAGMA 2021 Aug 4. Epub 2021 Aug 4.

Research Center for Molecular and Cellular Imaging, Advanced Medical Technologies and Instruments Institute (AMTII), Tehran University of Medical Sciences, Tehran, Iran.

Objective: To develop a decision-making tool to evaluate and compare the performance of neuroimaging markers with clinical findings and the significance of attributes for presurgical lateralization of mesial temporal lobe epilepsy (mTLE).

Methods: Thirty-five unilateral mTLE patients who qualified as candidates for surgical resection were studied. Seizure semiology, ictal EEG, ictal epileptogenic zone, interictal-irritative zone, and MRI findings were used as clinical markers. Read More

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Variations in pharmacokinetic-pharmacodynamic target values across MICs and their potential impact on determination of susceptibility test interpretive criteria.

J Antimicrob Chemother 2021 Aug 4. Epub 2021 Aug 4.

U.S. Food and Drug Administration, Office of Translational Sciences, Office of Clinical Pharmacology, Silver Spring, MD, USA.

Background: An antibacterial drug's susceptibility test interpretive criteria (STIC) are determined by integrating clinical, microbiological and pharmacokinetic-pharmacodynamic (PK-PD) data. PTA analysis plays a pivotal or supportive role in STIC determination and is heavily dependent on the PK-PD target values determined from animal PK-PD studies. Therefore, variations in PK-PD target values may impact STIC determination. Read More

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Comparison of the printed and online administration of the Behavioral Regulation in Exercise Questionnaire (BREQ-2).

Einstein (Sao Paulo) 2021 2;19:eAO6088. Epub 2021 Aug 2.

Instituto de Assistência Médica ao Servidor Público Estadual "Francisco Morato de Oliveira", São Paulo, SP, Brazil.

Objective: To compare the traditional printed form of the Behavioral Regulation in Exercise Questionnaire with a proposed online form in terms of validity, reliability, and applicability.

Methods: A crossover design study was conducted with 157 undergraduate students. Half of the sample answered the printed questionnaire first and then answered the online questionnaire 7 days later, while the other half of the sample did the inverse. Read More

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Perspective of nursing students about active learning and insertion in the job market.

Rev Bras Enferm 2021 30;74(6):e20190168. Epub 2021 Jul 30.

Faculdade de Medicina de Marília. Marília, São Paulo, Brazil.

Objective: to understand the perception of alumni from a nursing course which uses active learning methods about their insertion in the job market.

Methods: descriptive and exploratory study with a qualitative approach, carried out through 17 interviews with alumni from 2012 and 2014. The analysis took place using Dialectic Hermeneutics, as subsidized by the theoretical framework of the Theory of Complexity. Read More

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Construction of Genealogical Knowledge Graphs From Obituaries: Multitask Neural Network Extraction System.

J Med Internet Res 2021 Aug 4;23(8):e25670. Epub 2021 Aug 4.

School of Computer Science and Technology, Xi'an Jiaotong University, Xi'an, China.

Background: Genealogical information, such as that found in family trees, is imperative for biomedical research such as disease heritability and risk prediction. Researchers have used policyholder and their dependent information in medical claims data and emergency contacts in electronic health records (EHRs) to infer family relationships at a large scale. We have previously demonstrated that online obituaries can be a novel data source for building more complete and accurate family trees. Read More

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Smartphone Delivery of Cognitive Behavioral Therapy for Postintensive Care Syndrome-Family: Protocol for a Pilot Study.

JMIR Res Protoc 2021 Aug 4;10(8):e30813. Epub 2021 Aug 4.

Department of Surgery, Summa Health, Akron, OH, United States.

Background: Family members of critically ill patients experience symptoms of postintensive care syndrome-family (PICS-F), including anxiety, depression, and posttraumatic stress disorder. Postintensive care syndrome-family reduces the quality of life of the families of critically ill patients and may impede the recovery of such patients. Cognitive behavioral therapy has become a first-line nonpharmacological treatment of many psychological symptoms and disorders, including anxiety, depression, and posttraumatic stress. Read More

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A Worker-Centered Personal Health Record App for Workplace Health Promotion Using National Health Care Data Sets: Design and Development Study.

JMIR Med Inform 2021 Aug 4;9(8):e29184. Epub 2021 Aug 4.

Elecmarvels Co. Ltd., Daegu, Republic of Korea.

Background: Personal health record (PHR) technology can be used to support workplace health promotion, and prevent social and economic losses related to workers' health management. PHR services can not only ensure interoperability, security, privacy, and data quality, but also consider the user's perspective in their design.

Objective: Using Fast Healthcare Interoperability Resources (FHIR) and national health care data sets, this study aimed to design and develop an app for providing worker-centered, interconnected PHR services. Read More

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Influence of sample preparation optimization on the accuracy of dose assessment of an automatic non-fluorescent MN scoring system.

Int J Radiat Biol 2021 Aug 4:1-45. Epub 2021 Aug 4.

Institute of Nuclear Techniques, Budapest University of Technology and Economics, Budapest, Hungary.

Automatizing the scoring of the cytokinesis-blocked micronucleus assay spares a lot of valuable time. The dose-effect relationship can be applied reliably for dose estimation, if the quality of the slides is the same from the perspective of the used image processing algorithm. This aspect brings in additional requirements against the quality of the slides compared to the conventional visual scoring. Read More

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Screening for New Pathways in Atmospheric Oxidation Chemistry with Automated Mechanism Generation.

J Phys Chem A 2021 Aug 4. Epub 2021 Aug 4.

Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.

In the Earth's atmosphere, reactive organic carbon undergoes oxidation via a highly complex, multigeneration process, with implications for air quality and climate. Decades of experimental and theoretical studies, primarily on the reactions of hydrocarbons, have led to a canonical understanding of how gas-phase oxidation of organic compounds takes place. Recent research has brought to light a number of examples where the presence of certain functional groups opens up reaction pathways for key radical intermediates, including alkyl radicals, alkoxy radicals, and peroxy radicals, that are substantially different from traditional oxidation mechanisms. Read More

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Exploring the use of alginate hydrogel coating as a new initiative for emergent shoreline oiling prevention.

Sci Total Environ 2021 Jul 22;797:149234. Epub 2021 Jul 22.

Fisheries and Oceans Canada, Ecosystem Science, Ottawa, ON K1A 0E6, Canada.

Marine oil spills are often reported as a result of activities associated with oil exploration, production and transportation. The spilled oil may reach the shoreline, and then the stranded oil can persist for a long time, exerting many negative effects on coastal ecosystems. Conventional shoreline cleanup methods cannot effectively remove the oil residues from affected areas and are very expensive. Read More

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Assessment and improvement strategies of sustainable land management (SLM) planning initiative in Turkey.

Sci Total Environ 2021 Jul 21;797:149183. Epub 2021 Jul 21.

Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague, Czechia; The Forest Research Centre, School of Agriculture, University of Lisbon, Portugal. Electronic address:

Holistic planning and management of landscape is a prominent challenge. This paper provides a methodological framework for the assessment of an integrated land management plan with its action plans. Based on the scientific understanding, contemporary literature and the legal documents, a set of planning principles was developed and the strengths and weaknesses of the plan highlighted. Read More

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Role of Deep Learning in Early Detection of COVID-19: Scoping Review.

Comput Methods Programs Biomed Update 2021 Jul 30:100025. Epub 2021 Jul 30.

College of Science and Engineering, Hamad Bin Khalifa University, Doha, Qatar.

  Since the onset of the COVID-19 pandemic the world witnessed disruption on an unprecedented scale affecting our daily lives including but not limited to healthcare, business, education, and transportation. Deep Learning (DL) is a branch of Artificial intelligence (AI) applications, the recent growth of DL includes features that could be helpful in fighting the COVID-19 pandemic.. Read More

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