A machine learning based intelligent diagnosis and treatment model is proposed to address the urgent onset and rapid progression of hemorrhagic stroke,which often leads to mechanical damage to brain tissue and a series of complex physiological and pathological reactions.Firstly,artificial intelligence technology is used to process and analyze a large amount of image data.The model is applied to the clinical diagnosis and treatment of hemorrhagic stroke with randomly selected data.Compared with traditional methods,there are 62.08%,65.89%and 47.33%improvements in mean square error,mean absolute error and mean absolute percentage error,respectively.This model improves the accuracy of the prediction of hemorrhagic stroke patients.
维普
万方数据