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Application of Big Data Deep Learning in Auxiliary Diagnosis of Lower Extremity Arteriosclerosis Obliterans

At present, the incidence rate of arteriosclerosis obliterans (LEASO) of the lower extremities is significantly increased by aging and lifestyle changes. It is of great importance to predict the LEASO effectively and accurately by analyzing the imaging data of the lower extremities [1]. At this stage, China has entered the era of big data and artificial intelligence. Medical institutions at all levels can produce a large number of lower limb vascular image data every day. Using big data deep learning technology to intelligently analyze a large number of image data, and then carry out auxiliary diagnosis, so as to improve the diagnosis and treatment effect of LEASO is the focus of clinical research.