AIMC Topic: Clinical Trials as Topic

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Current status and limitations of artificial intelligence in colonoscopy.

United European gastroenterology journal
BACKGROUND: Artificial intelligence (AI) using deep learning methods for polyp detection (CADe) and characterization (CADx) is on the verge of clinical application. CADe already implied its potential use in randomized controlled trials. Further effor...

The case for AI-driven cancer clinical trials - The efficacy arm in silico.

Biochimica et biophysica acta. Reviews on cancer
Pharmaceutical agents in oncology currently have high attrition rates from early to late phase clinical trials. Recent advances in computational methods, notably causal artificial intelligence, and availability of rich clinico-genomic databases have ...

Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography.

Nature communications
Cancer patients have a higher risk of cardiovascular disease (CVD) mortality than the general population. Low dose computed tomography (LDCT) for lung cancer screening offers an opportunity for simultaneous CVD risk estimation in at-risk patients. Ou...

Moving Forward in the Next Decade: Radiation Oncology Sciences for Patient-Centered Cancer Care.

JNCI cancer spectrum
In a time of rapid advances in science and technology, the opportunities for radiation oncology are undergoing transformational change. The linkage between and understanding of the physical dose and induced biological perturbations are opening entire...

Utilizing Artificial Intelligence to Manage COVID-19 Scientific Evidence Torrent with Risklick AI: A Critical Tool for Pharmacology and Therapy Development.

Pharmacology
INTRODUCTION: The SARS-CoV-2 pandemic has led to one of the most critical and boundless waves of publications in the history of modern science. The necessity to find and pursue relevant information and quantify its quality is broadly acknowledged. Mo...

Evaluating eligibility criteria of oncology trials using real-world data and AI.

Nature
There is a growing focus on making clinical trials more inclusive but the design of trial eligibility criteria remains challenging. Here we systematically evaluate the effect of different eligibility criteria on cancer trial populations and outcomes ...

A knowledge base of clinical trial eligibility criteria.

Journal of biomedical informatics
OBJECTIVE: We present the Clinical Trial Knowledge Base, a regularly updated knowledge base of discrete clinical trial eligibility criteria equipped with a web-based user interface for querying and aggregate analysis of common eligibility criteria.

Nonparametric machine learning for precision medicine with longitudinal clinical trials and Bayesian additive regression trees with mixed models.

Statistics in medicine
Precision medicine is an active area of research that could offer an analytic paradigm shift for clinical trials and the subsequent treatment decisions based on them. Clinical trials are typically analyzed with the intent of discovering beneficial tr...

Deep Learning Approach to Parse Eligibility Criteria in Dietary Supplements Clinical Trials Following OMOP Common Data Model.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Dietary supplements (DSs) have been widely used in the U.S. and evaluated in clinical trials as potential interventions for various diseases. However, many clinical trials face challenges in recruiting enough eligible patients in a timely fashion, ca...