Potentials of AI in medical image analysis in Gastroenterology and Hepatology

Abstract

With the advancement of artificial intelligence (AI) technology, it comes in a big wave carrying possibly huge impact in the field of medicine. Gastroenterology and hepatology, being a specialty relying much on diagnostic imaging, endoscopy, and histopathology, AI technology has promised improving the quality and consistency of care to the patients. In this review, we will elucidate the development of machine learning methods, especially the visual representation mechanism in deep learning on recognition tasks. Various AI‐image analysis applications in endoscopy, radiology, and pathology are covered in gastroenterology and hepatology and reveal the enormous potentials for AI in assisting diagnosis, prognosis, and treatment. We also discuss the promises as well as pitfalls for AI in medical image analysis and pointing out future research directions.

Mapping ethico‐legal principles for the use of artificial intelligence in gastroenterology

“…Gastroenterology, like other areas of medicine, has the potential to revolutionize by AI‐assisted diagnosis, prognosis, and treatment. AI is already having a significant impact on gastroenterology through supervised use of AI‐imaging in endoscopy and colonoscopy 8 . AI‐assisted endoscopic examinations have been proven to work well in examination of the gut for lesions, polyps, and bleeding 9,10 .…”

“…While consent is undoubtedly central to health care, AI‐assisted interventions are ones where a fully informed consent may be difficult. Deep learning and machine neural networks will often operate in ways which are opaque, where the algorithms employed are nontransparent 8 . This black box problem raises fundamental challenges to the duty of medical professionals to explain the material risks of a course of treatment because the diagnosis, prognosis, and/or treatment choices are being made based on unknowable processes and determinations 16,17…”

“…AI is already having a significant impact on gastroenterology through supervised use of AI-imaging in endoscopy and colonoscopy. 8 AI-assisted endoscopic examinations have been proven to work well in examination of the gut for lesions, polyps, and bleeding. 9,10 AI-assisted colonoscopy is also being used in clinical practice to identify and characterize polyps.…”

Artificial Intelligence in Colorectal Polyp Detection and Characterization

“…Additionally, AI has utilized CT scans to determine tumor volume in patients with hepatocellular carcinoma [7]. While AI has also been applied to patient demographics and risk factors, much of the published AI research in gastroenterology has been in the field of medical image analysis (MIA) -a category of AI which analyzes different characteristics of an image to aid in diagnosis, prognosis, and intervention [8].…”

Artificial intelligence in gastrointestinal endoscopy

“…We stand at the threshold of a new era: the incorporation of artificial intelligence (AI) into routine gastrointestinal (GI) endoscopy practice to improve clinical performance. In this issue of Journal of Gastroenterology and Hepatology , review articles will address in depth the role of AI in medical image analysis in general and the use of AI in upper endoscopy, small bowel capsule endoscopy (CE), colonoscopy, and pancreatico‐biliary endoscopy in particular 1–5 …”