| Literature DB >> 33624891 |
Po-Ting Chen1, Dawei Chang2, Tinghui Wu2, Ming-Shiang Wu3,4, Weichung Wang2, Wei-Chih Liao3,4.
Abstract
The application of artificial intelligence (AI) in medicine has increased rapidly with respect to tasks including disease detection/diagnosis, risk stratification, and prognosis prediction. With recent advances in computing power and algorithms, AI has shown promise in taking advantage of vast electronic health data and imaging studies to supplement clinicians. Machine learning and deep learning are the most widely used AI methodologies for medical research and have been applied in pancreatobiliary diseases for which diagnosis and treatment selection are often complicated and require joint consideration of data from multiple sources. The aim of this review is to provide a concise introduction of the major AI methodologies and the current landscape of AI research in pancreatobiliary diseases.Entities:
Keywords: Artificial intelligence; Biliary disease; Pancreas
Year: 2021 PMID: 33624891 DOI: 10.1111/jgh.15380
Source DB: PubMed Journal: J Gastroenterol Hepatol ISSN: 0815-9319 Impact factor: 4.029