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Liver Diseases

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A pilot study for the prediction of liver function related scores using breath biomarkers and machine learning.

Scientific reports
Volatile organic compounds (VOCs) present in exhaled breath can help in analysing biochemical processes in the human body. Liver diseases can be traced using VOCs as biomarkers for physiological and pathophysiological conditions. In this work, we pro...

Investigating for bias in healthcare algorithms: a sex-stratified analysis of supervised machine learning models in liver disease prediction.

BMJ health & care informatics
OBJECTIVES: The Indian Liver Patient Dataset (ILPD) is used extensively to create algorithms that predict liver disease. Given the existing research describing demographic inequities in liver disease diagnosis and management, these algorithms require...

[Artificial intelligence technology enables ultrasonography in precision diagnosisand treatment of liver diseases].

Zhongguo xue xi chong bing fang zhi za zhi = Chinese journal of schistosomiasis control
Liver disease is one of the major problems affecting human health. Ultrasound plays an important role in diagnosis and treatment of diffuse and focal liver diseases. However, conventional ultrasound evaluation is subjective and provides limited infor...

A Deep Learning-Based Model for Predicting Abnormal Liver Function in Workers in the Automotive Manufacturing Industry: A Cross-Sectional Survey in Chongqing, China.

International journal of environmental research and public health
To identify the influencing factors and develop a predictive model for the risk of abnormal liver function in the automotive manufacturing industry works in Chongqing. Automotive manufacturing workers in Chongqing city surveyed during 2019-2021 were ...

Usefulness of Breath-Hold Fat-Suppressed T2-Weighted Images With Deep Learning-Based Reconstruction of the Liver: Comparison to Conventional Free-Breathing Turbo Spin Echo.

Investigative radiology
OBJECTIVES: The aim of this study was to evaluate the usefulness of breath-hold turbo spin echo with deep learning-based reconstruction (BH-DL-TSE) in acquiring fat-suppressed T2-weighted images (FS-T2WI) of the liver by comparing this method with co...

The potential role of machine learning in modelling advanced chronic liver disease.

Digestive and liver disease : official journal of the Italian Society of Gastroenterology and the Italian Association for the Study of the Liver
The use of artificial intelligence is rapidly increasing in medicine to support clinical decision making mostly through diagnostic and prediction models. Such models derive from huge databases (big data) including a large variety of health-related in...

Ultra-low-dose hepatic multiphase CT using deep learning-based image reconstruction algorithm focused on arterial phase in chronic liver disease: A non-inferiority study.

European journal of radiology
PURPOSE: This study determined whether image quality and detectability of ultralow-dose hepatic multiphase CT (ULDCT, 33.3% dose) using a vendor-agnostic deep learning model(DLM) are noninferior to those of standard-dose CT (SDCT, 100% dose) using mo...

Liver fat analysis using optimized support vector machine with support vector regression.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Fatty liver disease is a common condition caused by excess fat in the liver. It consists of two types: Alcoholic Fatty Liver Disease, also called alcoholic steatohepatitis, and Non-Alcoholic Fatty Liver Disease (NAFLD). As per epidemiolog...