作者
Vera Sorin, Benjamin S Glicksberg, Yaara Artsi, Yiftach Barash, Eli Konen, Girish N Nadkarni, Eyal Klang
发表日期
2024/3/19
来源
Journal of Cancer Research and Clinical Oncology
卷号
150
期号
3
页码范围
140
出版商
Springer Berlin Heidelberg
简介
Purpose
Despite advanced technologies in breast cancer management, challenges remain in efficiently interpreting vast clinical data for patient-specific insights. We reviewed the literature on how large language models (LLMs) such as ChatGPT might offer solutions in this field.
Methods
We searched MEDLINE for relevant studies published before December 22, 2023. Keywords included: “large language models”, “LLM”, “GPT”, “ChatGPT”, “OpenAI”, and “breast”. The risk bias was evaluated using the QUADAS-2 tool.
Results
Six studies evaluating either ChatGPT-3.5 or GPT-4, met our inclusion criteria. They explored clinical notes analysis, guideline-based question-answering, and patient management recommendations. Accuracy varied between studies, ranging from 50 to 98%. Higher accuracy was seen in structured tasks like information retrieval. Half of the studies used real patient data, adding practical clinical …
引用总数
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V Sorin, BS Glicksberg, Y Artsi, Y Barash, E Konen… - Journal of Cancer Research and Clinical Oncology, 2024