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United States Food and Drug Administration

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Evaluating a generative artificial intelligence accuracy in providing medication instructions from smartphone images.

Journal of the American Pharmacists Association : JAPhA
BACKGROUND: The Food and Drug Administration mandates patient labeling materials like the Medication Guide (MG) and Instructions for Use (IFU) to support appropriate medication use. However, challenges such as low health literacy and difficulties nav...

FDA-reviewed artificial intelligence-enabled products applicable to emergency medicine.

The American journal of emergency medicine
OBJECTIVE: To identify and assess artificial intelligence (AI)-enabled products reviewed by the U.S. Food and Drug Administration (FDA) that are potentially applicable to emergency medicine (EM).

Reimbursement and Regulatory Landscape for Artificial Intelligence in Medical Technology.

Gastrointestinal endoscopy clinics of North America
Integration of artificial intelligence (AI) into medical devices and services promises significant improvements in the diagnosis and treatment of disease. This article reviews current payment pathways for AI medical technology and the regulatory issu...

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...

Artificial intelligence and machine learning in veterinary medicine: a regulatory perspective on current initiatives and future prospects.

American journal of veterinary research
The US FDA's Center for Veterinary Medicine (CVM) is advancing its leadership in veterinary science by integrating AI and machine learning (ML) into its regulatory framework and scientific initiatives. This paper explores the CVM's strategic approach...

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...

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...

AI-Driven Analysis of Drug Marketing Efficiency: Unveiling FDA Approval to Market Release Dynamics.

The AAPS journal
This paper explores a novel approach using generative AI to enhance drug marketing strategies in the US pharmaceutical sector. By leveraging an official dataset sourced from the US government, the AI generates Python code to analyze the time interval...

Generalizability of FDA-Approved AI-Enabled Medical Devices for Clinical Use.

JAMA network open
IMPORTANCE: The primary objective of any newly developed medical device using artificial intelligence (AI) is to ensure its safe and effective use in broader clinical practice.

BoostDILI: Extreme Gradient Boost-Powered Drug-Induced Liver Injury Prediction and Structural Alerts Generation.

Chemical research in toxicology
Over the past 60 years, drug-induced liver injury (DILI) has played a key role in the withdrawal of marketed drugs due to safety concerns. Early prediction of DILI is crucial for developing safer pharmaceuticals, yet current and testing methods are...