Machine learning improves the prediction of significant fibrosis in Asian patients with metabolic dysfunction-associated steatotic liver disease - The Gut and Obesity in Asia (GO-ASIA) Study

• Main Authors: Verma, Nipun, Duseja, Ajay, Mehta, Manu, De, Arka, Lin, Huapeng, Wong, Vincent Wai-Sun, Wong, Grace Lai-Hung, Rajaram, Ruveena Bhavani, Chan, Wah-Kheong, Mahadeva, Sanjiv, Zheng, Ming-Hua, Liu, Wen-Yue, Treeprasertsuk, Sombat, Prasoppokakorn, Thaninee, Kakizaki, Satoru, Seki, Yosuke, Kasama, Kazunori, Charatcharoenwitthaya, Phunchai, Sathirawich, Phalath, Kulkarni, Anand, Purnomo, Hery Djagat, Kamani, Lubna, Lee, Yeong Yeh, Wong, Mung Seong, Tan, Eunice X. X., Young, Dan Yock
• Format: Article
• Published: Wiley 2024
• Subjects: R Medicine (General)
• Online Access: http://eprints.um.edu.my/45707/; https://doi.org/10.1111/apt.17891
• Institution: Universiti Malaya

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 mod...