Using Artificial Intelligence Methods for Detection of HCV-Caused Diseases
نویسندگان
چکیده
The Hepatitis C Virus (HCV) can cause chronic diseases and even lead to more serious conditions such as cirrhosis fibrosis. Early detection of HCV infection is crucial prevent these outcomes. However, in the early stages infection, when symptoms are not yet evident, patients rarely undergo testing. This highlights need for alternative materials guide testing disease. In this study, we investigate use artificial intelligence technology determine disease status individuals using blood data. A total 615 were included study. Preprocessing, filtering, feature selection, classification processes applied correlation method was used where features with high values selected given input five different algorithms. results study showed that K-Nearest Neighbor (KNN) algorithm achieved best success detecting patients, a rate 99.1%. research demonstrates be an effective tool HCV-related diseases. indicate KNN provide clear information about hepatitis from values. Future studies explore other AI techniques expand sample size improve accuracy model.
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ژورنال
عنوان ژورنال: Journal of engineering technology and applied sciences
سال: 2023
ISSN: ['2548-0391']
DOI: https://doi.org/10.30931/jetas.1216025