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Review

Role of Artificial Intelligence in Video Capsule Endoscopy

1
Endoscopy Unit, Digestive Diseases Centre, Queen’s Hospital, Barking Havering and Redbridge University Hospitals NHS Trust, Rom Valley Way, Romford, London RM7 0AG, UK
2
Photonics Group-Department of Physics, Imperial College London, Exhibition Rd, South Kensington, London SW7 2BX, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Vito Domenico Corleto
Diagnostics 2021, 11(7), 1192; https://doi.org/10.3390/diagnostics11071192
Received: 13 June 2021 / Accepted: 28 June 2021 / Published: 30 June 2021
(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
Capsule endoscopy (CE) has been increasingly utilised in recent years as a minimally invasive tool to investigate the whole gastrointestinal (GI) tract and a range of capsules are currently available for evaluation of upper GI, small bowel, and lower GI pathology. Although CE is undoubtedly an invaluable test for the investigation of small bowel pathology, it presents considerable challenges and limitations, such as long and laborious reading times, risk of missing lesions, lack of bowel cleansing score and lack of locomotion. Artificial intelligence (AI) seems to be a promising tool that may help improve the performance metrics of CE, and consequently translate to better patient care. In the last decade, significant progress has been made to apply AI in the field of endoscopy, including CE. Although it is certain that AI will find soon its place in day-to-day endoscopy clinical practice, there are still some open questions and barriers limiting its widespread application. In this review, we provide some general information about AI, and outline recent advances in AI and CE, issues around implementation of AI in medical practice and potential future applications of AI-aided CE. View Full-Text
Keywords: capsule endoscopy; artificial intelligence; deep learning capsule endoscopy; artificial intelligence; deep learning
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MDPI and ACS Style

Tziortziotis, I.; Laskaratos, F.-M.; Coda, S. Role of Artificial Intelligence in Video Capsule Endoscopy. Diagnostics 2021, 11, 1192. https://doi.org/10.3390/diagnostics11071192

AMA Style

Tziortziotis I, Laskaratos F-M, Coda S. Role of Artificial Intelligence in Video Capsule Endoscopy. Diagnostics. 2021; 11(7):1192. https://doi.org/10.3390/diagnostics11071192

Chicago/Turabian Style

Tziortziotis, Ioannis, Faidon-Marios Laskaratos, and Sergio Coda. 2021. "Role of Artificial Intelligence in Video Capsule Endoscopy" Diagnostics 11, no. 7: 1192. https://doi.org/10.3390/diagnostics11071192

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