AIMC Topic: United States

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Improvements to PTSD quality metrics with natural language processing.

Journal of evaluation in clinical practice May 24, 2021
RATIONALE AIMS AND OBJECTIVES: As quality measurement becomes increasingly reliant on the availability of structured electronic medical record (EMR) data, clinicians are asked to perform documentation using tools that facilitate data capture. These t...
United States Natural Language Processing Psychotherapy United States Department of Veterans Affairs Humans Electronic Health Records Stress Disorders, Post-Traumatic
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Recurrent Neural Networks to Automatically Identify Rare Disease Epidemiologic Studies from PubMed.

AMIA Joint Summits on Translational Science proceedings. AMIA Joint Summits on Translational Science May 17, 2021
Rare diseases affect between 25 and 30 million people in the United States, and understanding their epidemiology is critical to focusing research efforts. However, little is known about the prevalence of many rare diseases. Given a lack of automated ...
Epidemiologic Studies Humans Data Curation Neural Networks, Computer Rare Diseases United States PubMed
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Predicting Infective Endocarditis After Transcatheter Aortic Valve Implantation Via a Risk Model.

The American journal of cardiology May 9, 2021
Postoperative Complications United States Age Factors Predictive Value of Tests Machine Learning Female Risk Factors Humans Male Endocarditis Transcatheter Aortic Valve Replacement
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Diagnostic accuracy of current machine learning classifiers for age-related macular degeneration: a systematic review and meta-analysis.

Eye (London, England) May 6, 2021
BACKGROUND AND OBJECTIVE: The objective of this study was to systematically review and meta-analyze the diagnostic accuracy of current machine learning classifiers for age-related macular degeneration (AMD). Artificial intelligence diagnostic algorit...
Machine Learning Canada United States Fundus Oculi Macular Degeneration Humans Artificial Intelligence
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Comparative Effectiveness of Machine Learning Approaches for Predicting Gastrointestinal Bleeds in Patients Receiving Antithrombotic Treatment.

JAMA network open May 3, 2021
IMPORTANCE: Anticipating the risk of gastrointestinal bleeding (GIB) when initiating antithrombotic treatment (oral antiplatelets or anticoagulants) is limited by existing risk prediction models. Machine learning algorithms may result in superior pre...
Female Aged Aged, 80 and over Young Adult Adult Humans Machine Learning Retrospective Studies Clinical Decision-Making Fibrinolytic Agents Anticoagulants Atrial Fibrillation Venous Thromboembolism Myocardial Ischemia Thienopyridines Cross-Sectional Studies Male Middle Aged Adolescent Risk Assessment Cohort Studies United States Predictive Value of Tests Antifibrinolytic Agents Gastrointestinal Hemorrhage
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Discrepancies in Stroke Distribution and Dataset Origin in Machine Learning for Stroke.

Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association Apr 30, 2021
BACKGROUND: Machine learning algorithms depend on accurate and representative datasets for training in order to become valuable clinical tools that are widely generalizable to a varied population. We aim to conduct a review of machine learning uses i...
Machine Learning Data Accuracy Databases, Factual Prognosis Humans United States Prevalence Bias Stroke Data Mining
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Continual learning in medical devices: FDA's action plan and beyond.

The Lancet. Digital health Apr 28, 2021
Algorithms Delivery of Health Care Feedback United States United States Food and Drug Administration Humans Equipment and Supplies Machine Learning Medical Informatics Software Government Regulation
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Comparative study of machine learning methods for COVID-19 transmission forecasting.

Journal of biomedical informatics Apr 26, 2021
Within the recent pandemic, scientists and clinicians are engaged in seeking new technology to stop or slow down the COVID-19 pandemic. The benefit of machine learning, as an essential aspect of artificial intelligence, on past epidemics offers a new...
France Russia Saudi Arabia India United States Mexico COVID-19 Forecasting Brazil Deep Learning Humans Neural Networks, Computer Artificial Intelligence Machine Learning Pandemics
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Deep-learning based repurposing of FDA-approved drugs against dihydrofolate reductase and molecular dynamics study.

Journal of biomolecular structure & dynamics Apr 21, 2021
causes the fatal fungal bloodstream infection in humans called Candidiasis. Most of the species are resistant to the antifungals used to treat them. Drug-resistant poses very serious public health issues. To overcome this, the development of effec...
Benzodioxoles United States Food and Drug Administration Proline Lactams, Macrocyclic Drug Approval Rifampin Folic Acid Antagonists Candidiasis Aminopyridines Antifungal Agents United States Tetrahydrofolate Dehydrogenase Humans Molecular Dynamics Simulation Molecular Docking Simulation Sulfonamides Deep Learning Candida albicans Cyclopropanes Drug Repositioning
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Deep learning to detect acute respiratory distress syndrome on chest radiographs: a retrospective study with external validation.

The Lancet. Digital health Apr 20, 2021
BACKGROUND: Acute respiratory distress syndrome (ARDS) is a common, but under-recognised, critical illness syndrome associated with high mortality. An important factor in its under-recognition is the variability in chest radiograph interpretation for...
Humans Neural Networks, Computer Algorithms Retrospective Studies Female Aged Radiography Radiographic Image Interpretation, Computer-Assisted Datasets as Topic Radiography, Thoracic Deep Learning Pleural Cavity United States Pleural Diseases Respiratory Distress Syndrome Male Area Under Curve Middle Aged Lung Hospitals
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