Revolutionizing viral hepatitis management: Artificial intelligence-assisted diagnosis and personalized treatment

Table 1 Artificial intelligence techniques in viral hepatitis management

AI technique	Application	Accuracy/Achievement
Deep learning	Image analysis for liver abnormalities	High accuracy in detecting HCV-related lesions (Vijayakumar[1], 2023)
SVM and KNN algorithms	Patient classification based on liver function tests	High accuracy in HCV diagnosis (Hiyari et al[5], 2024) (Venkatesan et al[6], 2023)
Hybrid quantum neural networks	Early detection of HCV from CT scans	Improved accuracy and speed (Vijayakumar[1], 2023)
C5.0 algorithm with chi-square	HCV classification	96.75% accuracy (Mahmud et al[7], 2024)
Fuzzy Logic	HBV diagnosis	94.35% accuracy (Singh et al[14], 2024)
Genetic neural network	HBV diagnosis	99.14% accuracy (Singh and Kaur[14], 2024)

HCV: Hepatitis C virus; HBV: Hepatitis B virus; CT: Computed tomography; SVM: Support vector machine; KNN: K-Nearest Neighbor; C5.0: A decision tree algorithm for classification.