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Stream/Area:
-
Subject:
-
Paper ID:
IJSREM64890
Volume:
10 |
6 |
Jun 2026
Pages:
1-6
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
Master Of Computer Applications
GIET ENGINEERING COLLEGE
Master Of Computer Applications
GIET ENGINEERING COLLEGE
Liver disease is one of the major health problems affecting millions of people worldwide. Early detection is important because liver diseases often show very few symptoms in the beginning stages. If not identified early, they can lead to serious complications and affect a person's overall health. This project proposes a Liver Disease Prediction and Health Guidance System using Machine Learning. The system analyzes patient health information such as age, gender, bilirubin levels, protein levels, and other medical parameters to predict whether a person is at risk of liver disease. The system uses machine learning algorithms to classify patients into Low Risk, Medium Risk, and High Risk categories. Along with prediction results, the system also provides personalized health guidance and preventive suggestions. This helps patients understand their health condition and encourages early medical consultation. The proposed system aims to improve early diagnosis, reduce health risks, and support doctors in making better decisions.
KEYWORDS
The Liver Disease Prediction and Health Guidance System successfully combines machine learning techniques with healthcare assistance to provide early prediction of liver disease risk. The system helps users understand their health condition, encourages preventive healthcare practices and supports better medical decision-making. By providing prediction results along with personalized health recommendations the platform improves healthcare awareness and promotes healthier lifestyles.
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Publication Date
6/13/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
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