Abstract:

Liver disease is one of the leading causes of disease-related mortality worldwide, with survival rates heavily dependent on early detection and timely treatment. This project presents a Flask-based web application integrated with a machine learning model designed for early liver disease detection. The system employs a Random Forest Classifier trained on diverse patient health parameters, including liver function test results, demographic details, and clinical indicators, to assess an individual's risk of developing liver disease

Description:

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