A survey of machine learning applications in HIV clinical research and care

A growing trend in application of ML in HIV research was observed. The application paradigm has diversified to include practical clinical application, but statistical analysis remains the most dominant application. There is an increase in the use of genomic sources of data and high performance non-parametric ML methods with a focus on combating resistance to antiretroviral therapy (ART). There is need for improvement in collection of health records data and increased training in ML so as to translate ML research into clinical application in HIV management.