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United States Food and Drug Administration

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Evaluation of Natural Language Processing (NLP) systems to annotate drug product labeling with MedDRA terminology.

Journal of biomedical informatics
INTRODUCTION: The FDA Adverse Event Reporting System (FAERS) is a primary data source for identifying unlabeled adverse events (AEs) in a drug or biologic drug product's postmarketing phase. Many AE reports must be reviewed by drug safety experts to ...

Development of Decision Forest Models for Prediction of Drug-Induced Liver Injury in Humans Using A Large Set of FDA-approved Drugs.

Scientific reports
Drug-induced liver injury (DILI) presents a significant challenge to drug development and regulatory science. The FDA's Liver Toxicity Knowledge Base (LTKB) evaluated >1000 drugs for their likelihood of causing DILI in humans, of which >700 drugs wer...

Development of A Machine Learning Algorithm to Classify Drugs Of Unknown Fetal Effect.

Scientific reports
Many drugs commonly prescribed during pregnancy lack a fetal safety recommendation - called FDA 'category C' drugs. This study aims to classify these drugs into harmful and safe categories using knowledge gained from chemoinformatics (i.e., pharmacol...

Adverse Events in Robotic Surgery: A Retrospective Study of 14 Years of FDA Data.

PloS one
BACKGROUND: Use of robotic systems for minimally invasive surgery has rapidly increased during the last decade. Understanding the causes of adverse events and their impact on patients in robot-assisted surgery will help improve systems and operationa...

FDA Perspective on the Regulation of Artificial Intelligence in Health Care and Biomedicine.

JAMA
IMPORTANCE: Advances in artificial intelligence (AI) must be matched by efforts to better understand and evaluate how AI performs across health care and biomedicine as well as develop appropriate regulatory frameworks. This Special Communication revi...

A Machine Learning Algorithm to Predict Medical Device Recall by the Food and Drug Administration.

The western journal of emergency medicine
INTRODUCTION: Medical device recalls are important to the practice of emergency medicine, as unsafe devices include many ubiquitous items in emergency care, such as vascular access devices, ventilators, infusion pumps, video laryngoscopes, pulse oxim...

Implications of An Evolving Regulatory Landscape on the Development of AI and ML in Medicine.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
The rapid advancement of artificial intelligence and machine learning (AI/ML) technologies in healthcare presents significant opportunities for enhancing patient care through innovative diagnostic tools, monitoring systems, and personalized treatment...