AI Medical Compendium Topic

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Clinical Trials as Topic

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Swallowable, Remote- Controlled Robot Tours the Stomach, Transmits Live Video.

IEEE pulse
A pill-sized remote-operated vehicle that takes and transmits live video of the inside of a person's stomach could be on the market as early as 2026.

A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.

Neurology
BACKGROUND AND OBJECTIVES: Among the participants of Alzheimer disease (AD) treatment trials, 40% do not show cognitive decline over 80 weeks of follow-up. Identifying and excluding these individuals can increase power to detect treatment effects. We...

Public Disclosure of Results From Artificial Intelligence/Machine Learning Research in Health Care: Comprehensive Analysis of ClinicalTrials.gov, PubMed, and Scopus Data (2010-2023).

Journal of medical Internet research
BACKGROUND: Despite the rapid growth of research in artificial intelligence/machine learning (AI/ML), little is known about how often study results are disclosed years after study completion.

Large language models for automating clinical trial matching.

Current opinion in urology
PURPOSE OF REVIEW: The uses of generative artificial intelligence (GAI) technologies in medicine are expanding, with the use of large language models (LLMs) for matching patients to clinical trials of particular interest. This review provides an over...

AI meets informed consent: a new era for clinical trial communication.

JNCI cancer spectrum
Clinical trials are fundamental to evidence-based medicine, providing patients with access to novel therapeutics and advancing scientific knowledge. However, patient comprehension of trial information remains a critical challenge, as registries like ...

Enhancing clinical trial outcome prediction with artificial intelligence: a systematic review.

Drug discovery today
Clinical trials are pivotal in drug development yet fraught with uncertainties and resource-intensive demands. The application of AI models to forecast trial outcomes could mitigate failures and expedite the drug discovery process. This review discus...

A Tutorial and Use Case Example of the eXtreme Gradient Boosting (XGBoost) Artificial Intelligence Algorithm for Drug Development Applications.

Clinical and translational science
Approaches to artificial intelligence and machine learning (AI/ML) continue to advance in the field of drug development. A sound understanding of the underlying concepts and guiding principles of AI/ML implementation is a prerequisite to identifying ...

Agents for Change: Artificial Intelligent Workflows for Quantitative Clinical Pharmacology and Translational Sciences.

Clinical and translational science
Artificial intelligence (AI) is making a significant impact across various industries, including healthcare, where it is driving innovation and increasing efficiency. In the fields of Quantitative Clinical Pharmacology (QCP) and Translational Science...

Artificial intelligence in central-peripheral interaction organ crosstalk: the future of drug discovery and clinical trials.

Pharmacological research
Drug discovery before the 20th century often focused on single genes, molecules, cells, or organs, failing to capture the complexity of biological systems. The emergence of protein-protein interaction network studies in 2001 marked a turning point an...

AI-Driven Applications in Clinical Pharmacology and Translational Science: Insights From the ASCPT 2024 AI Preconference.

Clinical and translational science
Artificial intelligence (AI) is driving innovation in clinical pharmacology and translational science with tools to advance drug development, clinical trials, and patient care. This review summarizes the key takeaways from the AI preconference at the...