评估人工智能在提高乳腺癌管理多学科团队决策中的作用。

IF 1.7 Q4 ONCOLOGY
Merve Tokoçin, Turan Pehlivan, Selçuk Cin, Bülent Toksöz, Onur Tokoçin, Eda Cingöz, Nigar Erkoç, Aynur Özen, Nida Sünnetçi Arıkan, Şahin Bedir, Atilla Çelik
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引用次数: 0

摘要

目的:多学科团队(MDTs)对于优化乳腺癌治疗至关重要,但通用人工智能(AI),如ChatGPT,在支持这些团队中的作用仍未得到充分探索。本研究参照St. Gallen、European Society for Medical Oncology、National Comprehensive Cancer Network和American Society of Clinical Oncology的指南,将ChatGPT版本3.5和版本4与基于医院的MDT进行治疗和随访建议的比较。材料和方法:回顾性分析了2023年1月至2024年1月期间在 rkiye İstanbul一家培训医院连续诊断的100例乳腺癌患者。MDT提供基于共识的建议,而ChatGPT使用基于指南摘要的英文提示处理匿名患者数据。两位经验丰富的乳房外科医生在治疗后以5分制独立评估推荐的适宜性,重点关注临床结果,并使用加权的科恩kappa评估癌症分期、分子亚型和增殖指数的一致性。结果:ChatGPT-4(知识截止日期为2023年3月)与MDT基本一致(加权κ = 0.712),而ChatGPT-3.5显示中度一致(κ = 0.600)。对于额外的建议,如遗传咨询,一致性较低(GPT-4: κ = 0.398; GPT-3.5: κ = 0.302),与晚期或侵袭性病例相比,在早期和侵袭性较低的亚型中表现更好。在复杂或侵袭性病例中发现差异。结论:该研究表明,ChatGPT,特别是第4版,可以作为乳腺癌团队的辅助工具,特别是在早期病例中,尽管临床专业知识对于复杂情况仍然至关重要,需要进一步研究以完善人工智能集成。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluating the Role of Artificial Intelligence in Enhancing Multidisciplinary Team Decisions for Breast Cancer Management.

Objective: Multidisciplinary teams (MDTs) are essential for optimizing breast cancer treatment, yet the role of general-purpose artificial intelligence (AI), such as ChatGPT, in supporting these teams remains underexplored. This study compared ChatGPT versions 3.5 and 4 with a hospital-based MDT in making treatment and follow-up recommendations, using St. Gallen, European Society for Medical Oncology, National Comprehensive Cancer Network, and American Society of Clinical Oncology guidelines as a reference.

Materials and methods: A retrospective analysis of 100 consecutive breast cancer patients diagnosed between January 2023 and January 2024 at a training hospital in İstanbul, Türkiye, was conducted. The MDT provided consensus-based recommendations, while anonymized patient data were processed by ChatGPT using English prompts based on guideline summaries. Two experienced breast surgeons independently rated recommendation appropriateness on a five-point scale post-treatment, focusing on clinical outcomes, with agreement assessed using weighted Cohen's kappa across cancer stage, molecular subtype, and proliferation index.

Results: ChatGPT-4 (with a knowledge cut-off of March 2023) demonstrated substantial agreement with the MDT for primary treatments (weighted κ = 0.712), whereas ChatGPT-3.5 showed moderate agreement (κ = 0.600). Agreement for additional recommendations, such as genetic counseling, was lower (GPT-4: κ = 0.398; GPT-3.5: κ = 0.302), with better performance in early-stage and less aggressive subtypes compared to advanced or aggressive cases. Discrepancies were noted in complex or aggressive cases.

Conclusion: The study suggests ChatGPT, particularly version 4, may serve as a supportive tool for breast cancer teams, especially in early-stage cases, though clinical expertise remains vital for complex scenarios, warranting further research to refine AI integration.

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