AIMC Topic: United States Food and Drug Administration

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The current status and future of FDA-approved artificial intelligence tools in chest radiology in the United States.

Clinical radiology
Artificial intelligence (AI) is becoming more widespread within radiology. Capabilities that AI algorithms currently provide include detection, segmentation, classification, and quantification of pathological findings. Artificial intelligence softwar...

Utilizing Deep Learning for Detecting Adverse Drug Events in Structured and Unstructured Regulatory Drug Data Sets.

Pharmaceutical medicine
BACKGROUND: The US Food and Drug Administration (FDA) collects and retains several data sets on post-market drugs and associated adverse events (AEs). The FDA Adverse Event Reporting System (FAERS) contains millions of AE reports submitted by the pub...

Discovery of moiety preference by Shapley value in protein kinase family using random forest models.

BMC bioinformatics
BACKGROUND: Human protein kinases play important roles in cancers, are highly co-regulated by kinase families rather than a single kinase, and complementarily regulate signaling pathways. Even though there are > 100,000 protein kinase inhibitors, onl...

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...

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...

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.

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-...