Article

A Proof-of-Concept Large Language Model Application to Support Clinical Trial Screening in Surgical Oncology

2024-09-23

Abstract excerpt

<h4>Introduction</h4> Clinical trials advance the forefront of medical knowledge and rely on consistent patient accrual for success. However, patient screening for clinical trials is resource intensive. There is a need to increase the scalability of trial recruitment while maintaining or improving upon the sensitivity of the current process. We hypothesized we could use a state-of-the-art large language model (LLM...

Topics

Open a Topic to create a Post that cites this publication.

Identifiers and source

Literature Corpus work: b70e9fdf-a29e-5235-ac25-afc5da23c8e1
DOI: 10.1101/2024.09.20.24314053

Open publication

Related research

Semantic proximity does not establish scientific evidence.

Click a neighbor to travelStep 1 · 12 closest

A Proof-of-Concept Large Language Model Application to Support Clinical Trial Screening in Surgical OncologyDOI 10.1101/2024.09.20.24314053Read

Large Language Model Augmented Clinical Trial ScreeningSemantic proximity Read

Implementation of Human-in-the-Loop ChatGPT-based Patient Screening Across Multiple Diverse Clinical TrialsSemantic proximity Read

Utilizing Large Language Models for Enhanced Clinical Trial Matching: A Study on Automation in Patient ScreeningSemantic proximity Read

Analysis of Eligibility Criteria Clusters Based on Large Language Models for Clinical Trial DesignSemantic proximity Read

Enhancing Biomarker-Based Oncology Trial Matching Using Large Language ModelsSemantic proximity Read

SROTAS IQ: An AI-Based Clinical Trial Matching Platform: A Validation Study in Breast CancerSemantic proximity Read

Artificial Intelligence in Biomedical Data Analysis: A Comparative Assessment of Large Language Models for Automated Clinical Trial Interpretation and Statistical EvaluationSemantic proximity Read

Patient2Sentence: Semantic Compression of Clinical Trial Eligibility Using Large Language ModelsSemantic proximity Read

The TRIPOD-LLM Statement: A Targeted Guideline For Reporting Large Language Models UseSemantic proximity Read

A comparison of large language model versus manual chart review for extraction of data elements from the electronic health recordSemantic proximity Read

Inductive reasoning with large language models: a simulated randomized controlled trial for epilepsySemantic proximity Read

SEETrials: Leveraging Large Language Models for Safety and Efficacy Extraction in Oncology Clinical TrialsSemantic proximity Read