Diagnosis And Detection Of Hepatitis Disease Using ML

Swetha Talabathula, Gangotri Kongarani, Kala Devi Nadimpalli, Bhairava Varma Pesingi, Jaswanthi Korasikha, V. Sai Priya

Abstract


The main goal of this research is to determine the optimum method for diagnosing and identifying hepatitis while also taking future patient expectations into consideration. This study involved the completion of a comparative report between several machine learning technologies and neural networks. The precision rate and mean square error both affect the exhibition metric. The Machine Learning (ML) techniques, such as Support Vector Machines (SVM), K Nearest Neighbor (KNN), and Artificial Neural Network (ANN), were thought of as the characterising and anticipating tools for diagnosing hepatitis infection. In light of the accuracy of the sickness diagnosis prediction, a brief report on the aforementioned algorithms was completed.

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