AIMC Topic: Clinical Trials as Topic
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Machine learning prediction and explanatory models of serious infections in patients with rheumatoid arthritis treated with tofacitinib.
Arthritis research & therapy
Aug 27, 2024
BACKGROUND: Patients with rheumatoid arthritis (RA) have an increased risk of developing serious infections (SIs) vs. individuals without RA; efforts to predict SIs in this patient group are ongoing. We assessed the ability of different machine learn...
Zero- and few-shot prompting of generative large language models provides weak assessment of risk of bias in clinical trials.
Research synthesis methods
Aug 23, 2024
Existing systems for automating the assessment of risk-of-bias (RoB) in medical studies are supervised approaches that require substantial training data to work well. However, recent revisions to RoB guidelines have resulted in a scarcity of availabl...
Accelerating drug discovery, development, and clinical trials by artificial intelligence.
Med (New York, N.Y.)
Aug 21, 2024
Artificial intelligence (AI) has profoundly advanced the field of biomedical research, which also demonstrates transformative capacity for innovation in drug development. This paper aims to deliver a comprehensive analysis of the progress in AI-assis...
Machine learning and natural language processing in clinical trial eligibility criteria parsing: a scoping review.
Drug discovery today
Aug 19, 2024
Automatic eligibility criteria parsing in clinical trials is crucial for cohort recruitment leading to data validity and trial completion. Recent years have witnessed an explosion of powerful machine learning (ML) and natural language processing (NLP...
Mapping vaccine names in clinical trials to vaccine ontology using cascaded fine-tuned domain-specific language models.
Journal of biomedical semantics
Aug 10, 2024
BACKGROUND: Vaccines have revolutionized public health by providing protection against infectious diseases. They stimulate the immune system and generate memory cells to defend against targeted diseases. Clinical trials evaluate vaccine performance, ...
Prognostic enrichment for early-stage Huntington's disease: An explainable machine learning approach for clinical trial.
NeuroImage. Clinical
Aug 10, 2024
BACKGROUND: In Huntington's disease clinical trials, recruitment and stratification approaches primarily rely on genetic load, cognitive and motor assessment scores. They focus less on in vivo brain imaging markers, which reflect neuropathology well ...
AI-based automation of enrollment criteria and endpoint assessment in clinical trials in liver diseases.
Nature medicine
Aug 7, 2024
Clinical trials in metabolic dysfunction-associated steatohepatitis (MASH, formerly known as nonalcoholic steatohepatitis) require histologic scoring for assessment of inclusion criteria and endpoints. However, variability in interpretation has impac...
Integrating knowledge graphs into machine learning models for survival prediction and biomarker discovery in patients with non-small-cell lung cancer.
Journal of translational medicine
Aug 5, 2024
Accurate survival prediction for Non-Small Cell Lung Cancer (NSCLC) patients remains a significant challenge for the scientific and clinical community despite decades of advanced analytics. Addressing this challenge not only helps inform the critical...
Development of a differential treatment selection model for depression on consolidated and transformed clinical trial datasets.
Translational psychiatry
Jun 21, 2024
Major depressive disorder (MDD) is the leading cause of disability worldwide, yet treatment selection still proceeds via "trial and error". Given the varied presentation of MDD and heterogeneity of treatment response, the use of machine learning to u...
Virtual Clinical Trials: Implications of Computer Simulations and Artificial Intelligence for Musculoskeletal Research.
The Journal of bone and joint surgery. American volume
Jun 20, 2024
In silico clinical trials, particularly when augmented with artificial intelligence methods, represent an innovative approach with much to offer, particularly in the musculoskeletal field. They are a cost-effective, efficient, and ethical means of ev...
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