Artificial Intelligence in Gastroenterology: A Comprehensive Review
Artificial Intelligence (AI) is revolutionizing gastroenterology by enhancing diagnostic accuracy and streamlining endoscopic procedures in response to the growing prevalence of gastrointestinal diseases. This comprehensive review explores AI's transformative applications, particularly in gastr...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
National Board of Examinations
2025-06-01
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| Series: | National Board of Examinations Journal of Medical Sciences |
| Subjects: | |
| Online Access: | https://natboard.edu.in/ejournal/articledtl?x=cUhob2FmWUNtRWZQZGswMUY5QVFqQT09 |
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| Summary: | Artificial Intelligence (AI) is revolutionizing gastroenterology by enhancing diagnostic accuracy and streamlining endoscopic procedures in response to the growing prevalence of gastrointestinal diseases. This comprehensive review explores AI's transformative applications, particularly in gastrointestinal endoscopy, where it addresses critical challenges such as diagnostic 'miss rates' and the overwhelming volume of medical images. Through advanced technologies like Computer-Aided detection (CADe) and Computer-Aided diagnosis (CADx) using deep learning models, AI significantly improves polyp detection rates and reduces miss rates, with reported performances of 95% detection and 50% miss rate reduction. In capsule endoscopy, AI can significantly reduce reading time with improved algorithms to increase sensitivity and specificity in identifying gastrointestinal abnormalities. Additionally, AI plays a vital role in early oesophagal cancer detection by analyzing endoscopic images and distinguishing between dysplastic and non-dysplastic tissues. This review highlights AI's multifaceted benefits to Gastroenterology while noting limitations and future perspectives. As AI continues to evolve and integrate into clinical practice, it can enhance patient outcomes and significantly revolutionize diagnostic approaches in Gastroenterology. |
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| ISSN: | 2583-7524 |