Iason Psilopatis, Nadezda Sipulina, Frederik A Stuebs, Felix Heindl, Patrik Poeschke, Simon Bader, Annika Krueckel, Peter A Fasching, Matthias W Beckmann, Julius Emons
{"title":"人工智能在妇科肿瘤决策中的作用：可行性研究。","authors":"Iason Psilopatis, Nadezda Sipulina, Frederik A Stuebs, Felix Heindl, Patrik Poeschke, Simon Bader, Annika Krueckel, Peter A Fasching, Matthias W Beckmann, Julius Emons","doi":"10.1159/000544751","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>The objective of this study was to examine the potential of artificial intelligence (AI) in gynecologic oncology decision-making.</p><p><strong>Design: </strong>A feasibility study was conducted.</p><p><strong>Participants: </strong>Fictitious case vignettes of patients with gynecologic carcinomas were used.</p><p><strong>Setting: </strong>The setting was a fictive one.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Limitations: </strong>This study was limited to a feasibility study based on five fictitious case vignettes.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":12952,"journal":{"name":"Gynecologic and Obstetric Investigation","volume":" ","pages":"1-9"},"PeriodicalIF":2.0000,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Role of Artificial Intelligence in Gynecologic Oncology Decision-Making: A Feasibility Study.\",\"authors\":\"Iason Psilopatis, Nadezda Sipulina, Frederik A Stuebs, Felix Heindl, Patrik Poeschke, Simon Bader, Annika Krueckel, Peter A Fasching, Matthias W Beckmann, Julius Emons\",\"doi\":\"10.1159/000544751\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Objectives: </strong>The objective of this study was to examine the potential of artificial intelligence (AI) in gynecologic oncology decision-making.</p><p><strong>Design: </strong>A feasibility study was conducted.</p><p><strong>Participants: </strong>Fictitious case vignettes of patients with gynecologic carcinomas were used.</p><p><strong>Setting: </strong>The setting was a fictive one.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>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.</p><p><strong>Limitations: </strong>This study was limited to a feasibility study based on five fictitious case vignettes.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":12952,\"journal\":{\"name\":\"Gynecologic and Obstetric Investigation\",\"volume\":\" \",\"pages\":\"1-9\"},\"PeriodicalIF\":2.0000,\"publicationDate\":\"2025-02-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Gynecologic and Obstetric Investigation\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1159/000544751\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"OBSTETRICS & GYNECOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Gynecologic and Obstetric Investigation","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1159/000544751","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"OBSTETRICS & GYNECOLOGY","Score":null,"Total":0}
The Role of Artificial Intelligence in Gynecologic Oncology Decision-Making: A Feasibility Study.
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.
期刊介绍：
This journal covers the most active and promising areas of current research in gynecology and obstetrics. Invited, well-referenced reviews by noted experts keep readers in touch with the general framework and direction of international study. Original papers report selected experimental and clinical investigations in all fields related to gynecology, obstetrics and reproduction. Short communications are published to allow immediate discussion of new data. The international and interdisciplinary character of this periodical provides an avenue to less accessible sources and to worldwide research for investigators and practitioners.
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