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

ABSTRACT:

Background

The construction of a robust healthcare information system is fundamental to enhancing countries' capabilities in the surveillance and control of hepatitis B virus (HBV). Making use of China's rapidly expanding primary healthcare system, this innovative approach using big data and machine learning (ML) could help towards the World Health Organization's (WHO) HBV infection elimination goals of reaching 90% diagnosis and treatment rates by 2030. We aimed to develop and validate HBV detection models using routine clinical data to improve the detection of HBV and support the development of effective interventions to mitigate the impact of this disease in China.

Methods

Relevant data records extracted from the Family Medicine Clinic of the University of Hong Kong-Shenz

SUBMITTER: Dong W 

PROVIDER: S-EPMC10860422 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature