Artificial intelligence for computer assistance in endoscopic procedures and training

被引：0

作者：

Pablo Achurra ^{[1
]}

Domingo Mery ^{[4
]}

Arnoldo Riquelme ^{[2
]}

Chaya Shwaartz ^{[3
]}

机构：

[1] Pontificia Universidad Católica de Chile,Department of Digestive Surgery

[2] Pontificia Universidad Católica de Chile,Department of Computer Science

[3] Pontificia Universidad Católica de Chile,Department of Gastroenterology

[4] Toronto General Hospital,Department of Abdominal Transplant and HPB Surgical Oncology

[5] University of Toronto,undefined

来源：

Global Surgical Education - Journal of the Association for Surgical Education | / 4卷 / 1期

关键词：

Artificial intelligence; Endoscopy; Computer-aided detection; Computer vision; Training;

D O I：

10.1007/s44186-024-00336-4

中图分类号：

学科分类号：

摘要：

Artificial Intelligence (AI) will radically transform digestive endoscopy in the next decade. The assistance of computer-vision algorithms has very high performance in pattern recognition of endoscopic procedures and has been studied for detection, diagnosis, quality control, and endoscopic training. In upper endoscopy, AI algorithms have been developed to study malignant and non-malignant diseases of the esophagus and stomach with higher performance than human endoscopists. In wireless capsule imaging, AI may reduce reading times and increase efficiency. In colonoscopy, multiple studies have shown that algorithms can increase polyp detection by twofold and assist in diagnosing adenomas. AI can provide objective quality assessment and may shorten the learning curve of trainees. However, algorithm errors, medicolegal issues, and lack of applicability in different populations may limit the physician–AI collaboration. In this manuscript, we review the applications of AI in endoscopic procedures, its impact on endoscopy education, discuss its limitations, and describe the future of computer vision in gastroenterology.

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