Machine learning algorithm outperforms fibrosis markers in predicting significant fibrosis in biopsy‐confirmed NAFLD

Background The presence of significant liver fibrosis is a key determinant of long‐term prognosis in non‐alcoholic fatty liver disease (NAFLD). We aimed to develop a novel machine learning algorithm (MLA) to predict fibrosis severity in NAFLD and compared it with the most widely used non‐invasive fi...

Ausführliche Beschreibung

Bibliographische Detailangaben

Veröffentlicht in:	Journal of hepato-biliary-pancreatic sciences 2021-07, Vol.28 (7), p.593-603
Hauptverfasser:	Feng, Gong, Zheng, Kenneth I., Li, Yang‐Yang, Rios, Rafael S., Zhu, Pei‐Wu, Pan, Xiao‐Yan, Li, Gang, Ma, Hong‐Lei, Tang, Liang‐Jie, Byrne, Christopher D., Targher, Giovanni, He, Na, Mi, Man, Chen, Yong‐Ping, Zheng, Ming‐Hua
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Biopsy diagnosis fibrosis liver biopsy Machine learning machine learning algorithm NAFLD
Online-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!