1. Development of a diagnostic support system for the fibrosis of nonalcoholic fatty liver disease using artificial intelligence and deep learning
- Author
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Noppamate Preechathammawong, Mongkon Charoenpitakchai, Nutthawat Wongsason, Julalak Karuehardsuwan, Thaninee Prasoppokakorn, Panyavee Pitisuttithum, Anapat Sanpavat, Karn Yongsiriwit, Thannob Aribarg, Parkpoom Chaisiriprasert, Sombat Treeprasertsuk, and Sakkarin Chirapongsathorn
- Subjects
artificial intelligence ,digital histopathology ,liver fibrosis ,NAFLD: nonalcoholic fatty liver disease ,steatohepatitis ,Medicine (General) ,R5-920 - Abstract
Abstract Liver fibrosis is a pathological condition characterized by the abnormal proliferation of liver tissue, subsequently able to progress to cirrhosis or possibly hepatocellular carcinoma. The development of artificial intelligence and deep learning have begun to play a significant role in fibrosis detection. This study aimed to develop SMART AI‐PATHO, a fully automated assessment method combining quantification of histopathological architectural features, to analyze steatosis and fibrosis in nonalcoholic fatty liver disease (NAFLD) core biopsies and employ Metavir fibrosis staging as standard references and fat assessment grading measurement for comparison with the pathologist interpretations. There were 146 participants enrolled in our study. The correlation of Metavir scoring system interpretation between pathologists and SMART AI‐PATHO was significantly correlated (Agreement = 68%, Kappa = 0.59, p‐value
- Published
- 2024
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