Table 1_A machine learning-based predictive model for 48-week hepatitis B surface antigen seroclearance in chronic hepatitis B patients treated with pegylated interferon α-2b: prediction at week 24.doc

Table 1_A machine learning-based predictive model for 48-week hepatitis B surface antigen seroclearance in chronic hepatitis B patients treated with pegylated interferon α-2b: prediction at week 24.doc

Background<p>Chronic hepatitis B (CHB) is an infectious disease mainly affecting the liver, caused by the hepatitis B virus (HBV). In the treatment of CHB, pegylated interferon α-2b (PEG-IFNα-2b) is one of the important therapeutic options. However, there are significant individual differences...

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Détails bibliographiques
Auteur principal: Nan Kong (6917111) (author)
Autres auteurs: Kaixia Wang (5585582) (author), Yiling Wang (620129) (author), Shike Lou (14786614) (author), Luocheng Zhou (22474099) (author), Tao Wang (12008) (author), Zhili Tan (19196512) (author), Lihong Qu (2102689) (author)
Publié: 2025
Sujets:
Cell Biology
chronic hepatitis B
HBsAg seroclearance
predictive model
machine learning
clinical utility
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