{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T11:30:47Z","timestamp":1788348647612,"version":"build-2803163510"},"reference-count":26,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T00:00:00Z","timestamp":1749772800000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["obgyn.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Intl J Gynecology &amp; Obste"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>The rise of artificial intelligence (AI) and large language models like Llama, Gemini, or Generative Pretraining Transformer (GPT) signals a promising new era in natural language processing and has significant potential for application in medical care. This study seeks to investigate the potential of GPT\u20104 for automated therapy recommendations by examining individual patient health record data with a focus on gynecologic malignancies and breast cancer.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We tasked GPT\u20104 with generating independent treatment proposals for 60 randomly selected patient cases presented at gynecologic and senologic multidisciplinary tumor boards (MDTs). The treatment recommendations by GPT\u20104 were compared with those of the MDTs using a novel clinical concordance score and were reviewed both qualitatively and quantitatively by experienced gynecologic oncologists.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>GPT\u20104 generated coherent therapeutic recommendations for all clinical cases. Overall, these recommendations were assessed by clinical experts as moderately sufficient for real\u2010word clinical application. Deficiencies in both accuracy and completeness were especially noted. Using a quantitative clinical concordance score, GPT\u20104 consistently demonstrated superior performance in managing the senologic cases compared with the gynecologic cases. Iterative prompting substantially enhanced treatment recommendations in both categories, increasing concordance with MDT decisions to up to 84% in senologic cases.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusion<\/jats:title>\n                    <jats:p>GPT\u20104 is capable of processing complex patient cases and generates detailed treatment recommendations; however, differences persist in surgical approaches and the use of systemic therapies, and there is a tendency toward recommending excessive genetic testing. As AI\u2010powered solutions continue to be integrated into medicine, we envision the potential for automated therapy recommendations to play a supportive role in human clinical decision\u2010making in the future.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/ijgo.70251","type":"journal-article","created":{"date-parts":[[2025,6,13]],"date-time":"2025-06-13T10:50:33Z","timestamp":1749811833000},"page":"698-704","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Exploring the potential of\n                    <scp>AI<\/scp>\n                    \u2010powered applications for clinical decision\u2010making in gynecologic oncology"],"prefix":"10.1002","volume":"171","author":[{"given":"Bastian","family":"Meyer","sequence":"first","affiliation":[{"name":"Department of Gynecology and Obstetrics TUM University Hospital, Technical University Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Raphael","family":"Kfuri\u2010Rubens","sequence":"additional","affiliation":[{"name":"Institute of Computational Biology, Helmholtz Zentrum M\u00fcnchen, German Research Center for Environmental Health  Neuherberg Germany"},{"name":"Department of Medicine III, Hematology and Oncology TUM University Hospital, Technical University Munich  Munich Germany"},{"name":"TUM School of Medicine Technical University of Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Georg","family":"Schmidt","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics TUM University Hospital, Technical University Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Maliha","family":"Tariq","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics TUM University Hospital, Technical University Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Caroline","family":"Riedel","sequence":"additional","affiliation":[{"name":"Department of General Internal Medicine and Psychosomatics Heidelberg University Hospital  Heidelberg Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Florian","family":"Recker","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics Bonn University Hospital  Bonn Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fabian","family":"Riedel","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics Heidelberg University Hospital  Heidelberg Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Marion","family":"Kiechle","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics TUM University Hospital, Technical University Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9524-1514","authenticated-orcid":false,"given":"Maximilian","family":"Riedel","sequence":"additional","affiliation":[{"name":"Department of Gynecology and Obstetrics TUM University Hospital, Technical University Munich  Munich Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2025,6,13]]},"reference":[{"key":"e_1_2_11_2_1","unstructured":"TamkinA BrundageM ClarkJ GanguliD.Understanding the capabilities limitations and societal impact of large language models.2021arXiv:2102.02503. Available from:https:\/\/ui.adsabs.harvard.edu\/abs\/2021arXiv210202503T"},{"key":"e_1_2_11_3_1","doi-asserted-by":"crossref","unstructured":"DaiZ YangZ YangY CarbonellJ LeQV SalakhutdinovR.Transformer\u2010XL: attentive language models beyond a fixed\u2010length context.2019[arXiv:1901.02860 p.]. 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