OBJECTIVE: To examine the potential of artificial intelligence (AI) in gynecologic oncology decision making.

DESIGN: Feasibility study.

SETTING: Fictive.

PARTICIPANTS: Fictitious case vignettes of gynecologic carcinomas.

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 Chat-GPT 4.0, Google Gemini, and Bing-Copilot. Treatment approval decisions were based on standardized clinical and laboratory criteria.

RESULTS: Two cases of breast cancer, one case of ovarian cancer, one case of cervical cancer and one case of endometrial cancer were evaluated. All three language models were able to evaluate all clinical cases and make therapy-relevant suggestions, with Chat-GPT providing the most clear and concise recommendations that were in three cases totally consistent with physician assessments.

CONCLUSIONS: The study demonstrates that AI models, such as Chat-GPT, 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.

LIMITATIONS: Feasibility study with five fictitious case vignettes.