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Advocating for neurodata privacy and neurotechnology regulation.

The ability to record and alter brain activity by using implantable and nonimplantable neural device...

Navigating the AI Revolution: The Case for Precise Regulation in Health Care.

Health care is undergoing a profound transformation through the integration of artificial intelligen...

A comprehensive review of machine learning algorithms and their application in geriatric medicine: present and future.

The increasing access to health data worldwide is driving a resurgence in machine learning research,...

The Coming of Age of AI/ML in Drug Discovery, Development, Clinical Testing, and Manufacturing: The FDA Perspectives.

Artificial intelligence (AI) and machine learning (ML) represent significant advancements in computi...

Antimicrobial treatment imprecision: an outcome-based model to close the data-to-action loop.

Health-care systems, food supply chains, and society in general are threatened by the inexorable ris...

The 510(k) Third Party Review Program: Promise and Potential.

Every year, the Food and Drug Administration (FDA) clears approximately 3,000 medical devices for ma...

Multimodal deep learning as a next challenge in nutrition research: tailoring fermented dairy products based on -mediated lipid metabolism.

Deep learning is evolving in nutritional epidemiology to address challenges including precise nutrit...

Non-destructive optical sensing technologies for advancing the egg industry toward Industry 4.0: A review.

The egg is considered one of the best sources of dietary protein, and has an important role in human...

FDA Modernization Act 2.0: An insight from nondeveloping country.

Animal testing is required in drug development research and is crucial for assessing the efficacy an...

Deep-learning based detection of vessel occlusions on CT-angiography in patients with suspected acute ischemic stroke.

Swift diagnosis and treatment play a decisive role in the clinical outcome of patients with acute is...

FGFR1Pred: an artificial intelligence-based model for predicting fibroblast growth factor receptor 1 inhibitor.

Fibroblast growth factor receptors (FGFRs) are a family of cell surface receptors that bind to fibro...

Value Proposition of FDA-Approved Artificial Intelligence Algorithms for Neuroimaging.

PURPOSE: The number of FDA-cleared artificial intelligence (AI) algorithms for neuroimaging has grow...

Robotic Surgery in Urology: History from PROBOT to HUGO.

The advent of robotic surgical systems had a significant impact on every surgical area, especially u...

New drugs and stock market: a machine learning framework for predicting pharma market reaction to clinical trial announcements.

Pharmaceutical companies operate in a strictly regulated and highly risky environment in which a sin...

One-pot multicomponent synthesis of novel pyridine derivatives for antidiabetic and antiproliferative activities.

Due to the close relationship of diabetes with hypertension reported in various research, a set of ...

AndroPred: an artificial intelligence-based model for predicting androgen receptor inhibitors.

Androgen receptor (AR), a steroid receptor, plays a pivotal role in the pathogenesis of prostate can...

Classifying Free Texts Into Predefined Sections Using AI in Regulatory Documents: A Case Study with Drug Labeling Documents.

The US Food and Drug Administration (FDA) regulatory process often involves several reviewers who fo...

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