AI Medical Compendium Topic

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United States Food and Drug Administration

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When Medical Devices Have a Mind of Their Own: The Challenges of Regulating Artificial Intelligence.

American journal of law & medicine
How can an agency like the U.S. Food & Drug Administration ("FDA") effectively regulate software that is constantly learning and adapting to real-world data? Continuously learning algorithms pose significant public health risks if a medical device ca...

Unexpected Inequality: Disparate-Impact From Artificial Intelligence in Healthcare Decisions.

Journal of law and health
Systemic discrimination in healthcare plagues marginalized groups. Physicians incorrectly view people of color as having high pain tolerance, leading to undertreatment. Women with disabilities are often undiagnosed because their symptoms are dismisse...

Malfunction Events in the US FDA MAUDE Database: How Does Robotic Gynecologic Surgery Compare with Other Specialties?

Journal of minimally invasive gynecology
STUDY OBJECTIVE: To review malfunction events (MEs) related to the use of the da Vinci robot reported to the United States Food and Drug Administration Manufacturer and User Facility Device Experience in the last 10 years and compare gynecologic surg...

The role of machine learning in clinical research: transforming the future of evidence generation.

Trials
BACKGROUND: Interest in the application of machine learning (ML) to the design, conduct, and analysis of clinical trials has grown, but the evidence base for such applications has not been surveyed. This manuscript reviews the proceedings of a multi-...

Regulatory Issues and Challenges to Artificial Intelligence Adoption.

Radiologic clinics of North America
Artificial intelligence technology promises to redefine the practice of radiology. However, it exists in a nascent phase and remains largely untested in the clinical space. This nature is both a cause and consequence of the uncertain legal-regulatory...

FDA-regulated AI Algorithms: Trends, Strengths, and Gaps of Validation Studies.

Academic radiology
RATIONALE AND OBJECTIVES: To assess key trends, strengths, and gaps in validation studies of the Food and Drug Administration (FDA)-regulated imaging-based artificial intelligence/machine learning (AI/ML) algorithms.

Advancing pharmacy and healthcare with virtual digital technologies.

Advanced drug delivery reviews
Digitalisation of the healthcare sector promises to revolutionise patient healthcare globally. From the different technologies, virtual tools including artificial intelligence, blockchain, virtual, and augmented reality, to name but a few, are provid...

Trial Approach for Biomedical Products: A Regulatory Perspective.

Combinatorial chemistry & high throughput screening
The modern pharmaceutical industry is transitioning from traditional methods to advanced technologies like artificial intelligence. In the current scenario, continuous efforts are being made to incorporate computational modeling and simulation in dru...

The current status of breakthrough devices designation in the United States and innovative medical devices designation in Korea for digital health software.

Expert review of medical devices
INTRODUCTION: Artificial Intelligence (AI) is becoming increasingly utilized in the medical device industry as it can address unmet demands in clinical sites and provide more patient treatment options. This study aims to analyze the FDA's Breakthroug...