Machine learning model for non-alcoholic steatohepatitis diagnosis based on ultrasound radiomics.

ABSTRACT:

Background

Non-Alcoholic Steatohepatitis (NASH) is a crucial stage in the progression of Non-Alcoholic Fatty Liver Disease(NAFLD). The purpose of this study is to explore the clinical value of ultrasound features and radiological analysis in predicting the diagnosis of Non-Alcoholic Steatohepatitis.

Method

An SD rat model of hepatic steatosis was established through a high-fat diet and subcutaneous injection of CCl₄. Liver ultrasound images and elastography were acquired, along with serum data and histopathological results of rat livers.The Pyradiomics software was used to extract radiomic features from 2D ultrasound images of rat livers. The rats were then randomly divided into a training set and a validation set, and feature selection was performed through dimen

SUBMITTER: Xia F 

PROVIDER: S-EPMC11334577 | biostudies-literature | 2024 Aug

REPOSITORIES: biostudies-literature