A Big Data Disease Prediction System Based on 5G and Blockchain

Abstract

Embodiments of the present invention provide a big data disease prediction system and disease prediction method based on 5G and blockchain, aiming at automatic realization of disease prediction. Wherein, the method is applied to a server, and multiple disease prediction models for predicting different skin diseases are stored in the server, and the multiple models are divided into multiple groups, and multiple skin diseases predicted by each group of models have the same symptoms . The disease prediction method includes: receiving lesion images and text descriptions of disease symptoms; generating word vectors according to the text descriptions; comparing the word vectors with the respective sample word vectors of each group of disease prediction models, thereby determining the The closest sample word vector; call a group of disease prediction models corresponding to the sample word vector, and input the lesion image into each disease prediction model in the group of disease prediction models to obtain multiple prediction results, thereby determining the type of skin disease ; Feedback the skin disease type to the user terminal.

Description

technical field [0001] The present invention relates to the technical field of artificial intelligence, in particular to a big data disease prediction system and disease prediction method based on 5G and blockchain. Background technique [0002] With the application and popularization of the mobile Internet, more and more users start to conduct business online by means of mobile terminals. Taking the diagnosis of skin diseases through the telemedicine system as an example, the patient user usually needs to use a mobile terminal to take images of his own lesions and send them to the doctor's mobile terminal, so that the doctor can make a corresponding diagnosis based on the user's lesions. [0003] However, since the size of the patient group is usually much larger than that of the doctor group, after the patient sends the lesion image to the doctor, he usually needs to wait in line for the doctor's diagnosis, resulting in a long time-consuming disease diagnosis and low user ...

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Problems solved by technology

[0003] However, since the size of the patient group is usually much larger than that of the doctor group, after the patient sends the lesion image to the doctor, he usually needs to wait in line for the doctor's diagnosis, resulting in a long time-consuming disease diagnosis and low user experience.

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