Data-Centric Approach to Hepatitis C Virus Severity Prediction

Aniket Sharma, Ashok Arora, Anuj Gupta, Pramod Kumar Singh

Abstract: Every year, around 1.5 million of the world population succumbs to the Hepatitis C Virus. 70% of these cases develop chronic infection and cirrhosis within the next 20 years. Because there is no effective treatment for HCV, it is critical to predicting the virus in its early stages. The study’s goal is to define a data-driven approach for accurately detecting HCV severity in patients. Our approach achieves the highest accuracy of 86.79% compared to 70.89% using the standard approach.