{"title":"人工智能用于术后伤口监测:数字创新和临床可行性的综合综述。","authors":"Joel Grunhut, Khanjan Nagarsheth","doi":"10.1177/00031348251385104","DOIUrl":null,"url":null,"abstract":"<p><p>Artificial intelligence (AI) has transformative potential in postoperative wound care through precise, automated, and timely wound assessment, yet specific applications to surgical wounds remain relatively unexplored compared to chronic wound care. This integrative review critically assesses the state-of-the-art in AI-driven postoperative wound monitoring, highlighting significant advancements, existing limitations, and opportunities for future development. Following an extensive literature search of PubMed, Google Scholar, and Medline, we identified 118 relevant articles meeting stringent inclusion criteria. Our analysis underscores the critical need for large-scale, standardized datasets, explainable AI frameworks, and robust clinical validation studies. By evaluating AI technologies-such as deep learning, wearable biosensors, mobile applications, and natural language processing-we propose a roadmap for integrating advanced AI methods into surgical practice, aiming ultimately to enhance clinical outcomes and patient care.</p>","PeriodicalId":7782,"journal":{"name":"American Surgeon","volume":" ","pages":"31348251385104"},"PeriodicalIF":0.9000,"publicationDate":"2025-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence for Postoperative Wound Monitoring: An Integrative Review of Digital Innovation and Clinical Feasibility.\",\"authors\":\"Joel Grunhut, Khanjan Nagarsheth\",\"doi\":\"10.1177/00031348251385104\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Artificial intelligence (AI) has transformative potential in postoperative wound care through precise, automated, and timely wound assessment, yet specific applications to surgical wounds remain relatively unexplored compared to chronic wound care. This integrative review critically assesses the state-of-the-art in AI-driven postoperative wound monitoring, highlighting significant advancements, existing limitations, and opportunities for future development. Following an extensive literature search of PubMed, Google Scholar, and Medline, we identified 118 relevant articles meeting stringent inclusion criteria. Our analysis underscores the critical need for large-scale, standardized datasets, explainable AI frameworks, and robust clinical validation studies. By evaluating AI technologies-such as deep learning, wearable biosensors, mobile applications, and natural language processing-we propose a roadmap for integrating advanced AI methods into surgical practice, aiming ultimately to enhance clinical outcomes and patient care.</p>\",\"PeriodicalId\":7782,\"journal\":{\"name\":\"American Surgeon\",\"volume\":\" \",\"pages\":\"31348251385104\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2025-09-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"American Surgeon\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1177/00031348251385104\",\"RegionNum\":4,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"SURGERY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"American Surgeon","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1177/00031348251385104","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"SURGERY","Score":null,"Total":0}
Artificial Intelligence for Postoperative Wound Monitoring: An Integrative Review of Digital Innovation and Clinical Feasibility.
Artificial intelligence (AI) has transformative potential in postoperative wound care through precise, automated, and timely wound assessment, yet specific applications to surgical wounds remain relatively unexplored compared to chronic wound care. This integrative review critically assesses the state-of-the-art in AI-driven postoperative wound monitoring, highlighting significant advancements, existing limitations, and opportunities for future development. Following an extensive literature search of PubMed, Google Scholar, and Medline, we identified 118 relevant articles meeting stringent inclusion criteria. Our analysis underscores the critical need for large-scale, standardized datasets, explainable AI frameworks, and robust clinical validation studies. By evaluating AI technologies-such as deep learning, wearable biosensors, mobile applications, and natural language processing-we propose a roadmap for integrating advanced AI methods into surgical practice, aiming ultimately to enhance clinical outcomes and patient care.
期刊介绍:
The American Surgeon is a monthly peer-reviewed publication published by the Southeastern Surgical Congress. Its area of concentration is clinical general surgery, as defined by the content areas of the American Board of Surgery: alimentary tract (including bariatric surgery), abdomen and its contents, breast, skin and soft tissue, endocrine system, solid organ transplantation, pediatric surgery, surgical critical care, surgical oncology (including head and neck surgery), trauma and emergency surgery, and vascular surgery.