A Noninvasive Prediction Model for Hepatitis B Virus Disease in Patients with HIV: Based on the Population of Jiangsu, China.

Yi Yin Mingyue Xue Lingen Shi Tao Qiu Derun Xia Geng-Feng Fu Zhihang Peng

Published in: BioMed research international (2021)

The univariate logistics regression combined with the AdaBoost algorithm could accurately screen the risk factors of HBV in HIV coinfection without invasive testing. Further studies are needed to evaluate the utility and feasibility of this model in various settings.

Keyphrases

hepatitis b virus
antiretroviral therapy
hiv positive
hiv testing
hiv infected
risk factors
human immunodeficiency virus
hepatitis c virus
hiv aids
liver failure
men who have sex with men
machine learning
high throughput
deep learning
south africa