Cloud computing based disease self-diagnosis service construction system

Abstract

The invention discloses a cloud computing based disease self-diagnosis service construction system, which comprises a data resource collection module, a task planning module, a credible combination assessment module and a disease diagnosis model generation module, wherein the data resource collection module comprises a modeling submodule, a resource replication submodule and a resource search submodule, and the credible combination assessment module comprises an assessment submodule and an assessment optimization submodule. The cloud computing based disease self-diagnosis service construction system is provided with the data resource collection module, thereby facilitating users to use data resources through matching service description information, further increasing the coverage rate of data resource information in the network, and improving the search efficiency of medical record data resources; and the cloud computing based disease self-diagnosis service construction system is provided with the credible combination assessment module in order to efficiently realize low-cost disease self-diagnosis services, the credibility of a big data service supporting cloud service combination scheme is improved, and storage and computing resources of the cloud are utilized in a maximum benefit manner. In addition, the assessment time is saved, and the assessment speed is improved.

Description

technical field [0001] The invention relates to the medical field, in particular to a disease self-diagnosis service construction system based on cloud computing. Background technique [0002] The management of medical big data resources and the construction of medical big data services need to solve two technical problems: on the one hand, software applications in the medical field are generally developed by different vendors, based on different software and hardware platforms, in the underlying technology and business Extensive heterogeneity exists in terms of processes. Although these systems store a wealth of medical big data resources (such as electronic medical records, medical images, etc.), the phenomenon of information islands formed due to the heterogeneity between systems makes data sharing among different medical user groups very difficult. How to integrate the medical big data resources in these systems is a challenging problem; on the other hand, using these ...

AI Technical Summary

Problems solved by technology

Although these systems store a wealth of medical big data resources (such as electronic medical records, medical images, etc.), the phenomenon of information islands formed due to the heterogeneity between systems makes data sharing among different medical user groups very difficult

How to integrate medical big data resources in these systems is a challenging problem; on the other hand, using these rich medical big data resources to build medical big data services requires on-demand expansion of storage resources and computing resources. Support, bringing high cost investment and maintenance problems to the processing and analysis of big data and the construction of big data services

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