Journal
DIAGNOSTICS
Volume 11, Issue 7, Pages -Publisher
MDPI
DOI: 10.3390/diagnostics11071192
Keywords
capsule endoscopy; artificial intelligence; deep learning
Categories
Funding
- Hellenic Society of Gastroenterology for education in gastrointestinal endoscopy
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Capsule endoscopy is increasingly used in medical practice, but faces challenges and limitations. Artificial intelligence shows promise in improving CE performance and is likely to have a significant impact on endoscopy clinical practice in the future.
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.
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