Artificial Intelligence in Endoscopy Quality Measures - 26/02/25
Doi : 10.1016/j.giec.2024.10.001
Soban Maan, MD, Rohit Agrawal, MD, Shailendra Singh, MD, Shyam Thakkar, MD, FASGE ⁎ 
Division of Gastroenterology & Hepatology, Department of Medicine, West Virginia University, Morgantown, WV, USA
∗Corresponding author. Division of Gastroenterology & Hepatology, Department of Medicine, PO Box 9161, 5th Floor Health Sciences Center South, Suite 5500, Morgantown, WV 26506.Division of Gastroenterology & HepatologyDepartment of MedicinePO Box 91615th Floor Health Sciences Center SouthSuite 5500MorgantownWV26506
Résumé |
Quality of gastrointestinal endoscopy is a major determinant of its effectiveness. Artificial intelligence (AI) has the potential to enhance quality monitoring and improve endoscopy outcomes. This article reviews the current literature on AI algorithms that have been developed for endoscopy quality assessment.
Le texte complet de cet article est disponible en PDF.Keywords : Deep learning, Bowel preparation assessment, Withdrawal time monitoring, Blind spots, Inspection time, Quality metrics, Real-time quality monitoring
Plan
| Funding: This article was prepared without receipt of any funding. |
© 2024
Elsevier Inc. Tous droits réservés.
Vol 35 - N° 2
P. 431-444 - avril 2025 Retour au numéro
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