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Updated: Jul 3, 2025

Development of a Hepatitis B Virus Reporter System to Monitor the Early Stages of the Replication Cycle

Development of a Hepatitis B Virus Reporter System to Monitor the Early Stages of the Replication Cycle

Published on: February 1, 2017

Development and validation of HBV surveillance models using big data and machine learning.

Weinan Dong¹, Cecilia Clara Da Roza¹, Dandan Cheng²

¹Department of Family Medicine and Primary Care, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Hong Kong, China.

Annals of Medicine

|February 10, 2024

Summary

Machine learning models were developed using routine clinical data to improve hepatitis B virus (HBV) detection in China. These models can enhance HBV surveillance and support elimination goals.

Keywords:

Big data management China big data analytics infectious disease surveillance machine learning

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Published on: October 20, 2021

Area of Science:

Public Health
Medical Informatics
Machine Learning

Background:

Robust healthcare information systems are crucial for hepatitis B virus (HBV) surveillance and control.
China's primary healthcare system can leverage big data and machine learning (ML) to meet WHO HBV elimination goals.
Developing accurate HBV detection models is key to mitigating the disease's impact.

Purpose of the Study:

To develop and validate HBV detection models using routine clinical data.
To improve HBV detection rates within China's primary care setting.
To support the development of interventions for HBV control.

Main Methods:

Utilized Natural Language Processing (NLP) to structure clinical data from the University of Hong Kong-Shenzhen Hospital.
Developed and assessed multiple ML models for HBV risk assessment.
Validated models using a five-fold cross-validation framework and SHAP for interpretation.

Main Results:

Analyzed 27,392 cases from 158,988 clinic attendance records.
Developed a simplified HBV detection model with good discrimination (AUC = 0.78) and calibration.
Identified patterns in physical complaints associated with HBV infection.

Conclusions:

Developed HBV suspected case detection models for primary care settings in China.
These models show potential for clinical deployment to enhance HBV surveillance.
The findings contribute to improving HBV control strategies.