Big data medical learning method and system based on 5G and VR technologies

Abstract

The invention particularly relates to a big data medical learning method and system based on 5G and VR technologies. According to the big data medical learning method based on the 5G and VR technologies, a doctor of a superior hospital wears a small high-definition camera during diagnosis, treatment and operation, and the whole diagnosis, treatment and operation process of the doctor is shot in real time on the premise that the diagnosis, treatment and operation process is not affected; the shot video data is transmitted to a big data medical learning platform server by using a 5G communication network; doctors in lower-level hospitals wear VR glasses or helmets, hold VR handles by hands, watch videos for diagnosis and treatment or operations by using the VR glasses or the VR helmets, andcan simulate the operation process by using handheld VR devices. According to the big data medical learning method and system based on 5G and VR technologies, the learning cost of doctors of lower-level hospitals is reduced, the experience and practical operation level of the doctors of the lower-level hospitals can be rapidly and effectively improved, the overall improvement of the medical levelof the lower-level hospitals is achieved, and the medical pressure of superior hospitals is shared.

Description

technical field [0001] The present invention relates to the field of smart medical technology, in particular to a big data medical learning method and system based on 5G and VR technology. Background technique [0002] In our country, the phenomenon of uneven distribution of medical resources is relatively serious, and the superior resources are concentrated in a small number of regions and hospitals. Even if they are both Class 3 hospitals in provincial capital cities, the gap between hospitals is relatively large. Due to the gap between hospitals caused by force majeure factors such as geographical resources, when people have health problems, they will give priority to choosing better hospitals. On the one hand, it will increase the medical pressure on these hospitals; Trust prevents doctors from lower-level hospitals from growing well. When patients are diagnosed and treated, due to insufficient experience in lower-level hospitals, they cannot be diagnosed. At the same ti...

AI Technical Summary

Problems solved by technology

Due to the gap between hospitals caused by force majeure factors such as geographical resources, when people have health problems, they will give priority to choosing better hospitals. On the one hand, it will increase the medical pressure on these hospitals; Trust prevents doctors from lower-level hospitals from growing well. When patients are diagnosed and treated, due to insufficient experience in lower-level hospitals, they cannot be diagnosed. At the same time, patients' distrust of hospitals is deepened. level cannot be improved

[0003] At present, there is no such platform that allows doctors in lower-level hospitals to learn the diagnosis and treatment and surgical procedures of higher-level hospitals in real time, so as to improve their medical capabilities

Images