Automated quantification and architectural pattern detection of hepatic fibrosis in NAFLD.

ABSTRACT: Accurate detection and quantification of hepatic fibrosis remain essential for assessing the severity of non-alcoholic fatty liver disease (NAFLD) and its response to therapy in clinical practice and research studies. Our aim was to develop an integrated artificial intelligence-based automated tool to detect and quantify hepatic fibrosis and assess its architectural pattern in NAFLD liver biopsies. Digital images of the trichrome-stained slides of liver biopsies from patients with NAFLD and different severity of fibrosis were used. Two expert liver pathologists semi-quantitatively assessed the severity of fibrosis in these biopsies and using a web applet provided a total of 987 annotations of different fibrosis types for developing, training and testing supervised machine learning models t

SUBMITTER: Gawrieh S 

PROVIDER: S-EPMC8495470 | biostudies-literature | 2020 Aug

REPOSITORIES: biostudies-literature