Mori Yuichi, Hassan Cesare
Clinical Effectiveness Research Group, Faculty of Medicine, University of Oslo, Oslo, Norway.
Gastroenterology Section, Department of Transplantation Medicine, Oslo University Hospital, Oslo, Norway.
Clin Endosc. 2025 Jul;58(4):514-517. doi: 10.5946/ce.2024.338. Epub 2025 May 22.
Computer-aided diagnosis (CADx) in colonoscopy aims to improve the accuracy of diagnosing small polyps; however, its integration into clinical practice remains challenging. Human-artificial intelligence (AI) collaboration, which is expected to enhance optical diagnosis, has shown limited success in clinical trials, with studies indicating no significant improvement in human-only performance. Conversely, autonomous CADx systems that operate independently of clinicians have demonstrated superior diagnostic accuracy in some studies, suggesting their potential for efficiency, consistency, and standardization in healthcare. However, the adoption of autonomous AI raises ethical, legal, and practical concerns such as accountability for errors, loss of clinical context, and clinician or patient distrust. The decision between using CADx as an assistant or as an autonomous system may depend on the clinical scenario. Autonomous systems can standardize routine screening for low-risk patients, whereas assistive systems may complement expertise in complex cases. Regardless of the model used, robust regulatory frameworks and clinician training are essential to ensure safety and maintain trust. Balancing the strengths of AI with the critical role of human judgment is the key to optimizing outcomes and navigating the complex implications of integrating CADx technologies into colonoscopy practice.
结肠镜检查中的计算机辅助诊断(CADx)旨在提高小息肉诊断的准确性;然而,将其整合到临床实践中仍然具有挑战性。预期可增强光学诊断的人机协作在临床试验中的成效有限,研究表明仅靠人力操作的诊断性能并无显著改善。相反,独立于临床医生运行的自主CADx系统在一些研究中已展现出卓越的诊断准确性,这表明它们在医疗保健领域具有提高效率、保持一致性和实现标准化的潜力。然而,采用自主人工智能引发了伦理、法律和实际问题,如对错误负责、临床背景缺失以及临床医生或患者的不信任。选择将CADx用作辅助工具还是自主系统可能取决于临床情况。自主系统可使低风险患者的常规筛查标准化,而辅助系统则可在复杂病例中补充专业知识。无论使用哪种模式,强大的监管框架和临床医生培训对于确保安全和维持信任至关重要。平衡人工智能的优势与人类判断的关键作用是优化结果以及应对将CADx技术整合到结肠镜检查实践中的复杂影响的关键。