AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Eligibility Determination

Showing 11 to 20 of 28 articles

Clear Filters

Text Mining of the Electronic Health Record: An Information Extraction Approach for Automated Identification and Subphenotyping of HFpEF Patients for Clinical Trials.

Journal of cardiovascular translational research
Precision medicine requires clinical trials that are able to efficiently enroll subtypes of patients in whom targeted therapies can be tested. To reduce the large amount of time spent screening, identifying, and recruiting patients with specific subt...

Towards Phenotyping of Clinical Trial Eligibility Criteria.

Studies in health technology and informatics
BACKGROUND: Medical plaintext documents contain important facts about patients, but they are rarely available for structured queries. The provision of structured information from natural language texts in addition to the existing structured data can ...

Criteria2Query: a natural language interface to clinical databases for cohort definition.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Cohort definition is a bottleneck for conducting clinical research and depends on subjective decisions by domain experts. Data-driven cohort definition is appealing but requires substantial knowledge of terminologies and clinical data mode...

Artificial Intelligence Tool for Optimizing Eligibility Screening for Clinical Trials in a Large Community Cancer Center.

JCO clinical cancer informatics
PURPOSE: Less than 5% of patients with cancer enroll in clinical trials, and 1 in 5 trials are stopped for poor accrual. We evaluated an automated clinical trial matching system that uses natural language processing to extract patient and trial chara...

Participatory Design of a Clinical Trial Eligibility Criteria Simplification Method.

Studies in health technology and informatics
Clinical trial eligibility criteria are important for selecting the right participants for clinical trials. However, they are often complex and not computable. This paper presents the participatory design of a human-computer collaboration method for ...

A systematic review on natural language processing systems for eligibility prescreening in clinical research.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: We conducted a systematic review to assess the effect of natural language processing (NLP) systems in improving the accuracy and efficiency of eligibility prescreening during the clinical research recruitment process.

Evaluation of Criteria2Query: Towards Augmented Intelligence for Cohort Identification.

Studies in health technology and informatics
Electronic healthcare records data promises to improve the efficiency of patient eligibility screening, which is an important factor in the success of clinical trials and observational studies. To bridge the sociotechnical gap in cohort identificatio...

A review of research on eligibility criteria for clinical trials.

Clinical and experimental medicine
The purpose of this paper is to systematically sort out and analyze the cutting-edge research on the eligibility criteria of clinical trials. Eligibility criteria are important prerequisites for the success of clinical trials. It directly affects the...

Improving clinical trial design using interpretable machine learning based prediction of early trial termination.

Scientific reports
This study proposes using a machine learning pipeline to optimise clinical trial design. The goal is to predict early termination probability of clinical trials using machine learning modelling, and to understand feature contributions driving early t...