聊天新领域：用于感染监测的大型语言模型从试点到部署。

IF 3 4区医学 Q2 INFECTIOUS DISEASES

Infection Control and Hospital Epidemiology Pub Date : 2025-02-14 DOI:10.1017/ice.2025.20

Julie T Wu, Bradley J Langford, Erica S Shenoy, Evan Carey, Westyn Branch-Elliman

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引用次数: 0

摘要

Rodriguez-Nava等人提出了一项概念验证研究，评估了一种安全的大语言模型（LLM）的使用，该模型被批准用于医疗保健数据，用于回顾性识别特定的医疗保健相关感染(HAI)-中心线相关血流感染-从真实患者数据中进行监测这项研究为法学硕士如何至少实现半自动化或简化HAI监测活动指明了一个有希望的方向。

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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Chatting new territory: large language models for infection surveillance from pilot to deployment.

Rodriguez-Nava et al. present a proof-of-concept study evaluating the use of a secure large language model (LLM) approved for healthcare data for retrospective identification of a specific healthcare-associated infection (HAI)-central line-associated bloodstream infections-from real patient data for the purposes of surveillance.¹ This study illustrates a promising direction for how LLMs can, at a minimum, semi-automate or streamline HAI surveillance activities.

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来源期刊

Infection Control and Hospital Epidemiology 医学-传染病学

CiteScore

6.40

自引率

6.70%

发文量

289

审稿时长

3-8 weeks

期刊介绍： Infection Control and Hospital Epidemiology provides original, peer-reviewed scientific articles for anyone involved with an infection control or epidemiology program in a hospital or healthcare facility. Written by infection control practitioners and epidemiologists and guided by an editorial board composed of the nation''s leaders in the field, ICHE provides a critical forum for this vital information.