A Study on Cirrhosis Prediction Based on Machine Learning Techniques

Cirrhosis is an advanced stage of many chronic liver diseases, primarily caused by viral hepatitis. Early detection is crucial to prevent further liver tissue scarring and to prolong patient survival. AI-based computer-assisted diagnostics, utilizing Machine Learning ML and Deep Learning DL methods, offer significant advantages over conventional approaches by reducing time, effort, and risks. This paper aims to review recent key studies on diagnosing various liver diseases, with a focus on cirrhosis, using ML and DL techniques. Additionally, it will cover publicly accessible liver disorder datasets and metrics for evaluating model performance, and discuss existing research restrictions and future works for the automatic detection of cirrhosis.

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Publication Details

Journal
Journal of education for pure science.
Published
2024-12-01
DOI
https://doi.org/10.32792/jeps.v14i4.461
Citations
1
Primary Topic
Artificial Intelligence in Healthcare
Type
article
Field-Weighted Citation Impact
0.71
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article

A Study on Cirrhosis Prediction Based on Machine Learning Techniques

Maalim A. Aljabery, Duaa Sabeeh
1 citations
Journal of education for pure science.
Artificial Intelligence in Healthcare
0.71
article

A Study on Cirrhosis Prediction Based on Machine Learning Techniques

Maalim A. Aljabery, Duaa Sabeeh
article en
1 citations

Abstract

Cirrhosis is an advanced stage of many chronic liver diseases, primarily caused by viral hepatitis. Early detection is crucial to prevent further liver tissue scarring and to prolong patient survival. AI-based computer-assisted diagnostics, utilizing Machine Learning ML and Deep Learning DL methods, offer significant advantages over conventional approaches by reducing time, effort, and risks. This paper aims to review recent key studies on diagnosing various liver diseases, with a focus on cirrhosis, using ML and DL techniques. Additionally, it will cover publicly accessible liver disorder datasets and metrics for evaluating model performance, and discuss existing research restrictions and future works for the automatic detection of cirrhosis.

Journal of education for pure science.Vol. 14(4)
University of Basrah (IQ)
Good health and well-being
Openalex Percentile: Top 20%
Artificial Intelligence in Healthcare
0.71
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