Jennifer A Eckhoff, Dolores T Krauss, Stefanie Brunner, Christiane J Bruns, Hans F Fuchs
{"title":"[通过人工智能进行多模式数据处理:展望未来手术室]。","authors":"Jennifer A Eckhoff, Dolores T Krauss, Stefanie Brunner, Christiane J Bruns, Hans F Fuchs","doi":"10.1007/s00104-025-02377-x","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Despite intensive research the clinical implementation of artificial intelligence (AI) in surgery remains limited. In addition to infrastructural and regulatory barriers, this is due to the isolated processing of individual data sources (e.g. video), although the true potential of surgical AI lies in the integration of multimodal data.</p><p><strong>Objective: </strong>What added value does AI-driven analysis of multimodal data offer in surgery, and how can it realistically be integrated into clinical practice?</p><p><strong>Method: </strong>This review is based on first results on multimodal data acquisition and processing at University Hospital Cologne as well as a targeted literature search.</p><p><strong>Results: </strong>The integration of different data sources shows great potential; however, lack of infrastructure and regulation hinders the implementation.</p><p><strong>Discussion: </strong>In addition to technological development, clear legal frameworks are required to enable the clinical integration of innovative AI systems.</p>","PeriodicalId":72588,"journal":{"name":"Chirurgie (Heidelberg, Germany)","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2025-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"[Multimodal data processing through AI: envisioning the operating room of the future].\",\"authors\":\"Jennifer A Eckhoff, Dolores T Krauss, Stefanie Brunner, Christiane J Bruns, Hans F Fuchs\",\"doi\":\"10.1007/s00104-025-02377-x\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Despite intensive research the clinical implementation of artificial intelligence (AI) in surgery remains limited. In addition to infrastructural and regulatory barriers, this is due to the isolated processing of individual data sources (e.g. video), although the true potential of surgical AI lies in the integration of multimodal data.</p><p><strong>Objective: </strong>What added value does AI-driven analysis of multimodal data offer in surgery, and how can it realistically be integrated into clinical practice?</p><p><strong>Method: </strong>This review is based on first results on multimodal data acquisition and processing at University Hospital Cologne as well as a targeted literature search.</p><p><strong>Results: </strong>The integration of different data sources shows great potential; however, lack of infrastructure and regulation hinders the implementation.</p><p><strong>Discussion: </strong>In addition to technological development, clear legal frameworks are required to enable the clinical integration of innovative AI systems.</p>\",\"PeriodicalId\":72588,\"journal\":{\"name\":\"Chirurgie (Heidelberg, Germany)\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2025-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chirurgie (Heidelberg, Germany)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1007/s00104-025-02377-x\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chirurgie (Heidelberg, Germany)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s00104-025-02377-x","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
[Multimodal data processing through AI: envisioning the operating room of the future].
Background: Despite intensive research the clinical implementation of artificial intelligence (AI) in surgery remains limited. In addition to infrastructural and regulatory barriers, this is due to the isolated processing of individual data sources (e.g. video), although the true potential of surgical AI lies in the integration of multimodal data.
Objective: What added value does AI-driven analysis of multimodal data offer in surgery, and how can it realistically be integrated into clinical practice?
Method: This review is based on first results on multimodal data acquisition and processing at University Hospital Cologne as well as a targeted literature search.
Results: The integration of different data sources shows great potential; however, lack of infrastructure and regulation hinders the implementation.
Discussion: In addition to technological development, clear legal frameworks are required to enable the clinical integration of innovative AI systems.