Improving Hepatitis B outcome prediction with ensemble machine learning: A study on predictive models and interpretability.

Journal: Digital health
Published Date: Jun 16, 2025

Abstract

OBJECTIVE: Hepatitis B virus (HBV) is a significant global health threat, responsible for severe liver diseases such as liver failure, cirrhosis, and hepatocellular carcinoma. The burden is especially high in low-income regions, where early diagnosis and treatment are critical for mitigating its impact. This study investigates the effectiveness of various machine learning (ML) techniques in predicting patient outcomes in HBV infection.

Authors

  • Abid Bin Ahosan
    Department of Computer Science and Engineering, Dhaka International University, Dhaka, Bangladesh.
  • Forhadul Islam
    Department of Computer Science and Engineering, Dhaka International University, Dhaka, Bangladesh.
  • Khandaker Mohammad Mohi Uddin
    Department of Computer Science and Engineering, Southeast University, Dhaka, Bangladesh.
  • Nahid Hasan
    Department of Computer Science and Engineering, Southeast University, Dhaka, Bangladesh.
  • Md Ashraf Uddin
    School of Information Technology, Deakin University, Geelong 3125, Australia.

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