Feasibility of ultrasound radiomics based models for classification of liver fibrosis due to Schistosoma japonicum infection.

ABSTRACT:

Background

Schistosomiasis japonica represents a significant public health concern in South Asia. There is an urgent need to optimize existing schistosomiasis diagnostic techniques. This study aims to develop models for the different stages of liver fibrosis caused by Schistosoma infection utilizing ultrasound radiomics and machine learning techniques.

Methods

From 2018 to 2022, we retrospectively collected data on 1,531 patients and 5,671 B-mode ultrasound images from the Second People's Hospital of Duchang City, Jiangxi Province, China. The datasets were screened based on inclusion and exclusion criteria suitable for radiomics models. Liver fibrosis due to Schistosoma infection (LFSI) was categorized into four stages: grade 0, grade 1, grade 2, and grade 3. The data were d

SUBMITTER: Guo Z 

PROVIDER: S-EPMC11207143 | biostudies-literature | 2024 Jun

REPOSITORIES: biostudies-literature