The Role of Artificial Intelligence in Gynecologic Oncology Decision-Making: A Feasibility Study

Psilopatis I, Sipulina N, Stübs F, Heindl F, Pöschke P, Bader S, Krückel A, Fasching P, Beckmann M, Emons J (2025)

Publication Language: English

Publication Type: Journal article

Publication year: 2025

Journal

Gynecologic and Obstetric Investigation Karger

DOI: 10.1159/000544751

Abstract

Objectives: The objective of this study was to examine the potential of artificial intelligence (AI) in gynecologic oncology decision-making. Design: A feasibility study was conducted. Participants: Fictitious case vignettes of patients with gynecologic carcinomas were used. Setting: The setting was a fictive one. Methods: Fictitious case vignettes of gynecologic carcinomas were created and evaluated by physicians with varying levels of professional experience, as well as by language models including ChatGPT 4.0, Google Gemini, and Bing Copilot. Treatment approval decisions were based on standardized clinical and laboratory criteria. Results: Two cases of breast cancer, 1 case of ovarian cancer, 1 case of cervical cancer, and 1 case of endometrial cancer were evaluated. All three language models were able to evaluate all clinical cases and make therapy-relevant suggestions, with ChatGPT providing the most clear and concise recommendations that were in 3 cases totally consistent with physician assessments. Limitations: This study was limited to a feasibility study based on five fictitious case vignettes. Conclusions: The study demonstrates that AI models, such as ChatGPT, can to some extent evaluate clinical cases, recognize clinical and/or laboratory abnormalities, and make therapy-related suggestions. Despite high overall agreement, differences were predominantly noted in the more complex cases, rendering human interpretation necessary. The findings underscore the benefits of AI in terms of clarity, time efficiency, and cost-effectiveness. Future research should further explore the application of AI to real patient data and development of hybrid decision models to optimize integration into clinical practice.

Authors with CRIS profile

Frederik Stübs Department of Obstetrics and Gynaecology Felix Heindl Department of Obstetrics and Gynaecology Patrik Pöschke Department of Obstetrics and Gynaecology Simon Bader Department of Obstetrics and Gynaecology Annika Krückel Department of Obstetrics and Gynaecology Peter Fasching Professur für Translationale Frauenheilkunde und Geburtshilfe Matthias Beckmann Lehrstuhl für Geburtshilfe und Frauenheilkunde Julius Emons Department of Obstetrics and Gynaecology

Involved external institutions

Universitätsspital Basel CH Switzerland (CH)

How to cite

APA:

Psilopatis, I., Sipulina, N., Stübs, F., Heindl, F., Pöschke, P., Bader, S.,... Emons, J. (2025). The Role of Artificial Intelligence in Gynecologic Oncology Decision-Making: A Feasibility Study. Gynecologic and Obstetric Investigation. https://doi.org/10.1159/000544751

MLA:

Psilopatis, Iason, et al. "The Role of Artificial Intelligence in Gynecologic Oncology Decision-Making: A Feasibility Study." Gynecologic and Obstetric Investigation (2025).

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