Nipun Verma, Ajay Duseja, Manu Mehta, Arka De, Huapeng Lin, Vincent Wai-Sun Wong, Grace Lai-Hung Wong, Ruveena Bhavani Rajaram, Wah-Kheong Chan, Sanjiv Mahadeva, Ming-Hua Zheng, Wen-Yue Liu, Sombat Treeprasertsuk, Thaninee Prasoppokakorn, Satoru Kakizaki, Yosuke Seki, Kazunori Kasama, Phunchai Charatcharoenwitthaya, Phalath Sathirawich, Anand Kulkarni, Hery Djagat Purnomo, Lubna Kamani, Yeong Yeh Lee, Mung Seong Wong, Eunice X X Tan, Dan Yock Young
BACKGROUND: The precise estimation of cases with significant fibrosis (SF) is an unmet goal in non-alcoholic fatty liver disease (NAFLD/MASLD). AIMS: We evaluated the performance of machine learning (ML) and non-patented scores for ruling out SF among NAFLD/MASLD patients. METHODS: Twenty-one ML models were trained (N = 1153), tested (N = 283), and validated (N = 220) on clinical and biochemical parameters of histologically-proven NAFLD/MASLD patients (N = 1656) collected across 14 centres in 8 Asian countries...
February 1, 2024: Alimentary Pharmacology & Therapeutics