Data analysis method for multi-modal big data of clinical diseases

Abstract

The invention discloses a data analysis method for multi-modal big data of clinical diseases. The data analysis method includes the steps: acquiring historical big data corresponding to disease types from a medical system; designing a multi-density quantizer according to change rates of the historical big data in various modes; extracting characteristic information corresponding to the disease types from the historical big data by a multi-modal data mining method and a convolutional neural network method; deducing the dynamic evolution law of individuals infected by the disease types in the historical big data according to the characteristic information; acquiring performance evaluation indexes of real-time data according to the dynamic evolution law of the individuals. Therefore, the method effectively overcomes limitation of single-modal data, dangerous factors of diseases can be taken into full consideration, more detailed and accurate clinical diagnosis standards are provided for hospitals, the dynamic evolution law of the individuals can be given, decision basis and technical support are provided for early diagnosis and early treatment of the diseases, and diagnosis efficiency and diagnosis and treatment quality are improved.

Description

Technical field [0001] The invention relates to the field of medical data analysis, in particular to a data analysis method of multimodal big data for clinical diseases. Background technique [0002] With the development of society, science and technology continue to improve accordingly, and hospitals across the country have begun to diversify their data storage methods. Therefore, the concept of medical multi-modal big data has attracted the attention of experts and scholars. The multi-modal big data of clinical diseases refers to the collection of various data collected from different angles and visions (such as physiology, habits, psychology, environment, etc.) of diseases. Multi-modal big data provides new research ideas for the diagnosis and research of complex diseases. The massive multi-modal medical data contains information about the correlation between data and diseases. [0003] However, clinical diagnosis is mainly based on clinical manifestations and laboratory tests...

AI Technical Summary

Problems solved by technology

Moreover, this kind of error has an amplification effect as time goes on, and it will intensify, causing the evolution law to have a negative effect on the actual treatment effect.

Images