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

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.

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