Patients Facing Large Language Models in Oncology: A Narrative Review.

IF 3.3 Q2 ONCOLOGY JCO Clinical Cancer Informatics Pub Date : 2024-11-01 Epub Date: 2024-11-08 DOI:10.1200/CCI-24-00149
Charles Raynaud, David Wu, Jarod Levy, Matteo Marengo, Jean-Emmanuel Bibault
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引用次数: 0

Abstract

The integration of large language models (LLMs) into oncology is transforming patients' journeys through education, diagnosis, treatment monitoring, and follow-up. This review examines the current landscape, potential benefits, and associated ethical and regulatory considerations of the application of LLMs for patients in the oncologic domain.

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肿瘤学患者面对大型语言模型:叙述性综述。
将大型语言模型(LLMs)融入肿瘤学正在通过教育、诊断、治疗监测和随访改变患者的旅程。本综述探讨了在肿瘤学领域应用 LLMs 为患者服务的现状、潜在益处以及相关的伦理和监管考虑因素。
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
CiteScore
6.20
自引率
4.80%
发文量
190
期刊最新文献
Identifying Oncology Patients at High Risk for Potentially Preventable Emergency Department Visits Using a Novel Definition. Use of Patient-Reported Outcomes in Risk Prediction Model Development to Support Cancer Care Delivery: A Scoping Review. Optimizing End Points for Phase III Cancer Trials. Patients Facing Large Language Models in Oncology: A Narrative Review. Informatics and Artificial Intelligence-Guided Assessment of the Regulatory and Translational Research Landscape of First-in-Class Oncology Drugs in the United States, 2018-2022.
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