AIMC Topic: Clinical Trials as Topic
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Predicting therapeutic clinical trial enrollment for adult patients with low- and high-grade glioma using supervised machine learning.
Science advances
Jun 4, 2025
Therapeutic clinical trial enrollment does not match glioma incidence across demographics. Traditional statistical methods have identified independent predictors of trial enrollment; however, our understanding of the interactions between these factor...
Evaluating the Impact of AI-Based Model-Informed Drug Development (MIDD): A Comparative Review.
The AAPS journal
Jun 2, 2025
Model-informed drug development (MIDD) methods play critical role to ensure development of efficacious, and safe individualized therapies. The application of artificial intelligence/machine learning (AI/ML) within the field of drug development has ex...
Designing Clinical Trials for Patients With Rare Cancers: Connecting the Zebras.
American Society of Clinical Oncology educational book. American Society of Clinical Oncology. Annual Meeting
Apr 14, 2025
The field of rare cancer research is rapidly transforming, marked by significant progress in clinical trials and treatment strategies. Rare cancers, as defined by the National Cancer Institute, occur in fewer than 150 cases per million people each ye...
Artificial intelligence in central-peripheral interaction organ crosstalk: the future of drug discovery and clinical trials.
Pharmacological research
Apr 10, 2025
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...
Synthetic Data in Healthcare and Drug Development: Definitions, Regulatory Frameworks, Issues.
CPT: pharmacometrics & systems pharmacology
Apr 7, 2025
With the recent and evolving regulatory frameworks regarding the usage of Artificial Intelligence (AI) in both drug and medical device development, the differentiation between data derived from observed ('true' or 'real') sources and artificial data ...
A Machine Learning Approach to Predict Cognitive Decline in Alzheimer Disease Clinical Trials.
Neurology
Mar 25, 2025
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
Mar 21, 2025
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
Mar 20, 2025
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...
Utilising Natural Language Processing to Identify Brain Tumor Patients for Clinical Trials: Development and Initial Evaluation.
World neurosurgery
Mar 18, 2025
BACKGROUND: Identifying patients eligible for clinical trials through eligibility screening is time and resource-intensive. Natural Language Processing (NLP) models may enhance clinical trial screening by extracting data from Electronic Health Record...
Enhancing clinical trial outcome prediction with artificial intelligence: a systematic review.
Drug discovery today
Mar 15, 2025
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...
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