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Patient Selection

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Revolutionizing clinical trials: the role of AI in accelerating medical breakthroughs.

International journal of surgery (London, England)
Clinical trials are the essential assessment for safe, reliable, and effective drug development. Data-related limitations, extensive manual efforts, remote patient monitoring, and the complexity of traditional clinical trials on patients drive the ap...

Parsable Clinical Trial Eligibility Criteria Representation Using Natural Language Processing.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Successful clinical trials offer better treatments to current or future patients and advance scientific research. Clinical trials define the target population using specific eligibility criteria to ensure an optimal enrollment sample. Clinical trial ...

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...

Piloting an automated clinical trial eligibility surveillance and provider alert system based on artificial intelligence and standard data models.

BMC medical research methodology
BACKGROUND: To advance new therapies into clinical care, clinical trials must recruit enough participants. Yet, many trials fail to do so, leading to delays, early trial termination, and wasted resources. Under-enrolling trials make it impossible to ...

Patient selection for proton therapy using Normal Tissue Complication Probability with deep learning dose prediction for oropharyngeal cancer.

Medical physics
BACKGROUND: In cancer care, determining the most beneficial treatment technique is a key decision affecting the patient's survival and quality of life. Patient selection for proton therapy (PT) over conventional radiotherapy (XT) currently entails co...

Automated Matching of Patients to Clinical Trials: A Patient-Centric Natural Language Processing Approach for Pediatric Leukemia.

JCO clinical cancer informatics
PURPOSE: Matching patients to clinical trials is cumbersome and costly. Attempts have been made to automate the matching process; however, most have used a trial-centric approach, which focuses on a single trial. In this study, we developed a patient...

Enhancing site selection strategies in clinical trial recruitment using real-world data modeling.

PloS one
Slow patient enrollment or failing to enroll the required number of patients is a disruptor of clinical trial timelines. To meet the planned trial recruitment, site selection strategies are used during clinical trial planning to identify research sit...

Evaluation of an artificial intelligence-based clinical trial matching system in Chinese patients with hepatocellular carcinoma: a retrospective study.

BMC cancer
BACKGROUND: Artificial intelligence (AI)-assisted clinical trial screening is a promising prospect, although previous matching systems were developed in English, and relevant studies have only been conducted in Western countries. Therefore, we evalua...

[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening].

Bulletin du cancer
INTRODUCTION: The recruitment step of all clinical trials is time consuming, harsh and generate extra costs. Artificial intelligence tools could improve recruitment in order to shorten inclusion phase. The objective was to assess the performance of a...