Navigating Gynecological Oncology with Different Versions of ChatGPT: A Transformative Breakthrough or the Next Black Box Challenge?

IF 2 4区 医学 Q3 ONCOLOGY Oncology Research and Treatment Pub Date : 2024-12-17 DOI:10.1159/000543173
Nur Dokuzeylul Gungor, Fatih Sinan Esen, Tolga Tasci, Kagan Gungor, Kaan Cil
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Abstract

Introduction: The study evaluates the performance of large language model versions of ChatGPT - ChatGPT-3.5, ChatGPT-4, and ChatGPT-Omni - in addressing inquiries related to the diagnosis and treatment of gynecological cancers, including ovarian, endometrial, and cervical cancers.

Methods: A total of 804 questions were equally distributed across four categories: true/false, multiple-choice, open-ended, and case-scenario, with each question type representing varying levels of complexity. Performance was assessed using a six-point Likert scale, focusing on accuracy, completeness, and alignment with established clinical guidelines.

Results: For true/false queries, ChatGPT-Omni achieved accuracy rates of 100% for easy, 98% for medium, and 97% for complicated questions, higher than ChatGPT-4 (94%, 90%, 85%) and ChatGPT-3.5 (90%, 85%, 80%) (p = 0.041, 0.023, 0.014, respectively). In multiple-choice, ChatGPT-Omni maintained superior accuracy with 100% for easy, 98% for medium, and 93% for complicated queries, compared to ChatGPT-4 (92%, 88%, 80%) and ChatGPT-3.5 (85%, 80%, 70%) (p = 0.035, 0.028, 0.011). For open-ended questions, ChatGPT-Omni had mean Likert scores of 5.8 for easy, 5.5 for medium, and 5.2 for complex levels, outperforming ChatGPT-4 (5.4, 5.0, 4.5) and ChatGPT-3.5 (5.0, 4.5, 4.0) (p = 0.037, 0.026, 0.015). Similar trends were observed in case-scenario questions, where ChatGPT-Omni achieved scores of 5.6, 5.3, and 4.9 for easy, medium, and hard levels, respectively (p = 0.017, 0.008, 0.012).

Conclusions: ChatGPT-Omni exhibited superior performance in responding to clinical queries related to gynecological cancers, underscoring its potential utility as a decision support tool and an educational resource in clinical practice.

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用不同版本的ChatGPT导航妇科肿瘤学:一个变革性的突破还是下一个黑匣子挑战?
本研究评估了chatgpt -3.5、ChatGPT-4和chatgpt - omniin的大语言模型(LLM)版本在解决妇科癌症(包括卵巢癌、子宫内膜癌和宫颈癌)诊断和治疗相关查询中的性能。方法:共804个问题平均分布在四个类别:真假、选择题、开放式和案例-场景,每个问题类型代表不同的复杂程度。使用6分李克特量表评估表现,重点是准确性、完整性和与既定临床指南的一致性。结果:对于真假查询,ChatGPT-Omni在简单问题上的准确率为100%,在中等问题上的准确率为98%,在复杂问题上的准确率为97%,高于ChatGPT-4(94%, 90%, 85%)和ChatGPT-3.5 (90%, 85%, 80%) (p分别=0.041,0.023,0.014)。在多项选择中,与ChatGPT-4(92%, 88%, 80%)和ChatGPT-3.5(85%, 80%, 70%)相比,ChatGPT-Omni在简单查询中保持了100%的准确率,在中等查询中保持了98%,在复杂查询中保持了93%的准确率(p=0.035, 0.028, 0.011)。对于开放式问题,ChatGPT-Omni的平均李克特分数为简单5.8分,中等5.5分,复杂5.2分,优于ChatGPT-4(5.4, 5.0, 4.5)和ChatGPT-3.5 (5.0, 4.5, 4.0) (p=0.037, 0.026, 0.015)。在Case-Scenario问题中也观察到类似的趋势,ChatGPT-Omni在简单、中等和困难水平上分别获得了5.6、5.3和4.9分(p=0.017、0.008、0.012)。结论:ChatGPT-Omni在回答妇科癌症相关的临床问题方面表现优异,强调了其作为决策支持工具和临床实践中的教育资源的潜在效用。
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来源期刊
CiteScore
3.20
自引率
0.00%
发文量
84
期刊介绍: With the first issue in 2014, the journal ''Onkologie'' has changed its title to ''Oncology Research and Treatment''. By this change, publisher and editor set the scene for the further development of this interdisciplinary journal. The English title makes it clear that the articles are published in English – a logical step for the journal, which is listed in all relevant international databases. For excellent manuscripts, a ''Fast Track'' was introduced: The review is carried out within 2 weeks; after acceptance the papers are published online within 14 days and immediately released as ''Editor’s Choice'' to provide the authors with maximum visibility of their results. Interesting case reports are published in the section ''Novel Insights from Clinical Practice'' which clearly highlights the scientific advances which the report presents.
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