Abstract: Liver diseases constitute a major global health challenge, responsible for millions of deaths each year and placing a substantial burden on healthcare systems. The liver is a vital organ responsible for metabolic regulation, detoxification, and biochemical synthesis. Any disruption in its functioning can lead to severe disorders such as Hepatitis, Cirrhosis, Liver Cancer, Non-Alcoholic Fatty Liver Disease (NAFLD), and Alcoholic Liver Disease. Early detection of these conditions is crucial because most liver disorders progress silently, showing minimal or non-specific symptoms during their initial stages. Traditional diagnostic methods, including blood tests, imaging scans, and biopsies, are often invasive, costly, time-consuming, and may not always provide clear or timely results. These limitations highlight the need for accurate, efficient, and automated tools that can support clinical decision-making.


Downloads: PDF | DOI: 10.17148/IJARCCE.2025.141183

How to Cite:

[1] Smruti Suresh Mahajan, Prof. Shivam Limbare, Manoj V. Nikum, "Liver Disease Prediction Using Machine Learning," International Journal of Advanced Research in Computer and Communication Engineering (IJARCCE), DOI: 10.17148/IJARCCE.2025.141183

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