Leveraging artificial intelligence for evidence-based recommendations in uterine fibroid therapy: Addressing the unmet need in German healthcare—A clinical trial

Psilopatis I, Lotz L, Sipulina N, Heindl F, Levidou G, Emons J (2025)

Publication Language: English

Publication Type: Journal article

Publication year: 2025

Journal

International Journal of Gynecology & Obstetrics Elsevier

DOI: 10.1002/ijgo.70407

Abstract

Objective: To evaluate the potential of an artificial intelligence (AI)-driven large language model, ChatGPT 4.0, to provide personalized, evidence-based treatment recommendations for uterine fibroids. Methods: ChatGPT 4.0 was trained using evidence-based data from Uptodate and German medical literature. The algorithm generated individualized recommendations based on clinical characteristics and patient preferences. Usability and quality were assessed through questionnaires completed by 40 gynecologists and 45 women with fibroids. Results: Most gynecologists found the algorithm user-friendly and comprehensive, with 15 expressing a willingness to integrate it into practice and 24 acknowledging its potential to enhance healthcare efficiency. Although only half believed it would improve patient outcomes, the tool was generally well received. Patients found the algorithm easy to understand and helpful for exploring treatment options, with the majority feeling it empowered informed discussions with their healthcare providers. A minority expressed dissatisfaction with usability or helpfulness. Conclusion: ChatGPT 4.0 offers a promising AI-driven tool for personalized fibroid management in the absence of formal guidelines. Although not a substitute for official recommendations, it could support clinical decision making and enhance patient education. Further integration with standardized guidelines and prospective trials is needed to optimize its clinical utility.

Authors with CRIS profile

Laura Lotz Department of Obstetrics and Gynaecology Felix Heindl Department of Obstetrics and Gynaecology Julius Emons Department of Obstetrics and Gynaecology

Involved external institutions

Universitätsspital Basel CH Switzerland (CH) Paracelsus Medizinische Privatuniversität, Nürnberg DE Germany (DE)

How to cite

APA:

Psilopatis, I., Lotz, L., Sipulina, N., Heindl, F., Levidou, G., & Emons, J. (2025). Leveraging artificial intelligence for evidence-based recommendations in uterine fibroid therapy: Addressing the unmet need in German healthcare—A clinical trial. International Journal of Gynecology & Obstetrics. https://doi.org/10.1002/ijgo.70407

MLA:

Psilopatis, Iason, et al. "Leveraging artificial intelligence for evidence-based recommendations in uterine fibroid therapy: Addressing the unmet need in German healthcare—A clinical trial." International Journal of Gynecology & Obstetrics (2025).

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