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...

Full description

Saved in:
Bibliographic Details
Main Author: Nan Kong (6917111) (author)
Other Authors: 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)
Published: 2025
Subjects:
Cell Biology
chronic hepatitis B
HBsAg seroclearance
predictive model
machine learning
clinical utility
Tags: Add Tag
No Tags, Be the first to tag this record!

Similar Items

Similar Items