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CC BY-NC-ND 4.0 · Journal of Digestive Endoscopy 2020; 11(04): 245-252
DOI: 10.1055/s-0040-1717824
Review Article

Artificial Intelligence in Small Bowel Endoscopy: Current Perspectives and Future Directions

Dinesh Meher
1   Department of Gastroenterology, S.C.B. Medical College, Cuttack, Odisha, India
,
Mrinal Gogoi
1   Department of Gastroenterology, S.C.B. Medical College, Cuttack, Odisha, India
,
Pankaj Bharali
1   Department of Gastroenterology, S.C.B. Medical College, Cuttack, Odisha, India
,
Prajna Anirvan
1   Department of Gastroenterology, S.C.B. Medical College, Cuttack, Odisha, India
,
Shivaram Prasad Singh
1   Department of Gastroenterology, S.C.B. Medical College, Cuttack, Odisha, India
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Abstract

Artificial intelligence (AI) is a computer system that is able to perform tasks which normally require human intelligence. The role of AI in the field of gastroenterology has been gradually evolving since its inception in the 1950s. Discovery of wireless capsule endoscopy (WCE) and balloon enteroscopy (BE) has revolutionized small gut imaging. While WCE is a relatively patient-friendly and noninvasive mode to examine the nonobstructed small gut, it is limited by a lengthy examination time and the need for expertise in reading images acquired by the capsule. Similarly, BE, despite having the advantage of therapeutic intervention, is costly, invasive, and requires general sedation. Incorporation of concepts like machine learning and deep learning has been used to handle large amounts of data and images in gastroenterology. Interestingly, in small gut imaging, the application of AI has been limited to WCE only. This review was planned to examine and summarize available published data on various AI-based approaches applied to small bowel disease.

We conducted an extensive literature search using Google search engine, Google Scholar, and PubMed database for published literature in English on the application of different AI techniques in small bowel endoscopy, and have summarized the outcome and benefits of these applications of AI in small bowel endoscopy. Incorporation of AI in WCE has resulted in significant advancements in the detection of various lesions starting from dysplastic mucosa, inflammatory and nonmalignant lesions to the detection of bleeding with increasing accuracy and has shortened the lengthy review time in image analysis. As most of the studies to evaluate AI are retrospective, the presence of inherent selection bias cannot be excluded. Besides, the interpretability (black-box nature) of AI models remains a cause for concern. Finally, issues related to medical ethics and AI need to be judiciously addressed to enable its seamless use in future.

Keywords

artificial intelligence - machine learning - deep learning - wireless capsule endoscopy - balloon enteroscopy - artificial neural network - convolutional neural network


Publikationsverlauf

Artikel online veröffentlicht:
08. Oktober 2020

© 2020. Society of Gastrointestinal Endoscopy of India. This is an open access article published by Thieme under the terms of the Creative Commons Attribution-NonDerivative-NonCommercial-License, permitting copying and reproduction so long as the original work is given appropriate credit. Contents may not be used for commercial purposes, or adapted, remixed, transformed or built upon. (https://creativecommons.org/licenses/by-nc-nd/4.0/).

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