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Machine Learning for Liver Disease Prediction by mubtasim.ahmed.2 is a document available to read on EtoBox.

What is Machine Learning for Liver Disease Prediction about?

The literature review compares various machine learning models for predicting liver disease, highlighting that SVM, logistic regression, and decision trees achieve accuracies of 85%, 82%, and 79%, respectively. Additionally, a study found that random forest outperformed other algorithms with an accuracy of 87.5% for fatty liver prediction, while a hybrid voting classifier achieved the highest accuracy of 92.5% for fibrosis and cirrhosis. Overall, the findings suggest that combining different data types and

Author

mubtasim.ahmed.2

Language

EN