Practical Aspects of Using Large Language Models to Screen Abstracts for Cardiovascular Drug Development: Cross-Sectional Study.

IF 3.1 3区医学 Q2 MEDICAL INFORMATICS

JMIR Medical Informatics Pub Date : 2024-09-30 DOI:10.2196/64143

Jay G Ronquillo, Jamie Ye, Donal Gorman, Adina R Lemeshow, Stephen J Watt

引用次数: 0

Abstract

Unlabelled: Cardiovascular drug development requires synthesizing relevant literature about indications, mechanisms, biomarkers, and outcomes. This short study investigates the performance, cost, and prompt engineering trade-offs of 3 large language models accelerating the literature screening process for cardiovascular drug development applications.

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使用大型语言模型筛选心血管药物开发摘要的实用方面：横断面研究。

无标签：心血管药物开发需要综合有关适应症、机制、生物标记物和结果的相关文献。这项简短的研究调查了 3 个大型语言模型的性能、成本和及时工程权衡，这些模型可加速心血管药物开发应用的文献筛选过程。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

JMIR Medical Informatics Medicine-Health Informatics

CiteScore

7.90

自引率

3.10%

发文量

173

审稿时长

12 weeks

期刊介绍： JMIR Medical Informatics (JMI, ISSN 2291-9694) is a top-rated, tier A journal which focuses on clinical informatics, big data in health and health care, decision support for health professionals, electronic health records, ehealth infrastructures and implementation. It has a focus on applied, translational research, with a broad readership including clinicians, CIOs, engineers, industry and health informatics professionals. Published by JMIR Publications, publisher of the Journal of Medical Internet Research (JMIR), the leading eHealth/mHealth journal (Impact Factor 2016: 5.175), JMIR Med Inform has a slightly different scope (emphasizing more on applications for clinicians and health professionals rather than consumers/citizens, which is the focus of JMIR), publishes even faster, and also allows papers which are more technical or more formative than what would be published in the Journal of Medical Internet Research.