AIMC Topic: United States Food and Drug Administration

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Approval of artificial intelligence and machine learning-based medical devices in the USA and Europe (2015-20): a comparative analysis.

The Lancet. Digital health Jan 18, 2021
There has been a surge of interest in artificial intelligence and machine learning (AI/ML)-based medical devices. However, it is poorly understood how and which AI/ML-based medical devices have been approved in the USA and Europe. We searched governm...
Machine Learning Databases, Factual United States Humans Artificial Intelligence Equipment and Supplies Device Approval Biomedical Technology Government Regulation Europe Radiology United States Food and Drug Administration
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Applications of artificial intelligence in drug development using real-world data.

Drug discovery today Dec 24, 2020
The US Food and Drug Administration (FDA) has been actively promoting the use of real-world data (RWD) in drug development. RWD can generate important real-world evidence reflecting the real-world clinical environment where the treatments are used. M...
United States Food and Drug Administration Humans Machine Learning Artificial Intelligence Animals United States Deep Learning Drug Development Drug Repositioning
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Industry ties and evidence in public comments on the FDA framework for modifications to artificial intelligence/machine learning-based medical devices: a cross sectional study.

BMJ open Oct 14, 2020
OBJECTIVES: To determine the extent and disclosure of financial ties to industry and use of scientific evidence in comments on a US Food and Drug Administration (FDA) regulatory framework for modifications to artificial intelligence/machine learning ...
Artificial Intelligence Disclosure Machine Learning Cross-Sectional Studies Humans Conflict of Interest United States United States Food and Drug Administration Drug Industry
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The first use of artificial intelligence (AI) in the ER: triage not diagnosis.

Emergency radiology Jul 8, 2020
Predictions related to the impact of AI on radiology as a profession run the gamut from AI putting radiologists out of business to having no effect at all. The use of AI appears to show significant promise in ER triage in the present. We briefly disc...
United States Food and Drug Administration United States Emergency Service, Hospital Triage Diagnostic Imaging Humans Radiology Artificial Intelligence
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Machine learning for pattern detection in cochlear implant FDA adverse event reports.

Cochlear implants international Jul 5, 2020
Medical device performance and safety databases can be analyzed for patterns and novel opportunities for improving patient safety and/or device design. The objective of this analysis was to use supervised machine learning to explore patterns in rep...
United States Food and Drug Administration Cochlear Implantation Equipment Failure Analysis Logistic Models United States Bayes Theorem Cochlear Implants Public Reporting of Healthcare Data Algorithms Databases, Factual Female Adult Male Child Humans Machine Learning
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Artificial Intelligence in Emergency Medicine: Surmountable Barriers With Revolutionary Potential.

Annals of emergency medicine Feb 21, 2020
Humans Neural Networks, Computer Artificial Intelligence Patient-Centered Care United States Food and Drug Administration United States Emergency Medicine Delivery of Health Care Triage Deep Learning Emergency Service, Hospital Canada
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Policy Implications of Artificial Intelligence and Machine Learning in Diabetes Management.

Current diabetes reports Feb 1, 2020
PURPOSE OF REVIEW: Machine learning (ML) is increasingly being studied for the screening, diagnosis, and management of diabetes and its complications. Although various models of ML have been developed, most have not led to practical solutions for rea...
Mass Screening Health Policy United States Food and Drug Administration Machine Learning United States Diabetes Mellitus Humans Artificial Intelligence
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Machine learning-based identification and rule-based normalization of adverse drug reactions in drug labels.

BMC bioinformatics Dec 23, 2019
BACKGROUND: Use of medication can cause adverse drug reactions (ADRs), unwanted or unexpected events, which are a major safety concern. Drug labels, or prescribing information or package inserts, describe ADRs. Therefore, systematically identifying A...
Neural Networks, Computer Drug Labeling Drug-Related Side Effects and Adverse Reactions Data Mining United States Food and Drug Administration Machine Learning Deep Learning United States
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The role of AI in diagnosing lung diseases.

The Lancet. Respiratory medicine Sep 26, 2019
United States Food and Drug Administration Information Dissemination Role Humans Male Artificial Intelligence United States Female Lung Diseases
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Predictive Analysis of First Abbreviated New Drug Application Submission for New Chemical Entities Based on Machine Learning Methodology.

Clinical pharmacology and therapeutics Jun 12, 2019
Generic drug products are approved by the US Food and Drug Administration (FDA) through Abbreviated New Drug Applications (ANDAs). The ANDA review and approval involves multiple offices across the FDA. Forecasting ANDA submissions can critically info...
Drugs, Generic Humans Resource Allocation United States Machine Learning United States Food and Drug Administration Time Factors Drug Approval
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