Hypertensive intracerebral hemorrhage(HICH)is a disease with a rapid onset,rapid progression,high mortality rate,and long-term impact on the ability to function.Non-contrast agent-based CT(NCCT)is a common method for evaluating and identifying HICH.Recent radiomics in image processing and machine learning(ML)have enabled the extraction of high-dimensional feature information from medical images,which can be used to rapidly and accurately diagnose HICH and predict its course of disease.The paper describes the application of radiomics and ML techniques in HICH diagnosis and treatment,and identifies possible directions for future research.