Medical self-diagnosis service design method based on credible combination assessment under big data

Abstract

The invention discloses a medical self-diagnosis service design method based on credible combination assessment under big data. The method comprises the following steps of analyzing an application mode corresponding to a basic self-diagnosis service and a big data processing flow related to a process of building a disease self-diagnosis service; decomposing a big data processing task into a set of functionally-independent sub-tasks, and forming a task planning scheme of building the disease self-diagnosis service; using a credible combination assessment method to select a cloud service combination scheme with the optimal QoS for the disease self-diagnosis service based on the requirement of each sub-task on computing resources and storage resources in the task planning scheme; and achieving a big data analysis algorithm of the disease self-diagnosis service in the cloud service corresponding to each sub-task, thus completing deployment and execution of the disease self-diagnosis service. According to the method provided by the invention, the big data about electronic medical records acquired by searching is stored, and subjected to online retrieval and processing and analysis, so that the user can call the disease self-diagnosis service on line to acquire disease self-diagnosis help.

Description

technical field [0001] The invention relates to the technical field of medical diagnosis, in particular to a method for designing medical self-diagnosis services based on credible combination evaluation under big data. Background technique [0002] A large part of the current medical contradiction is the contradiction between the limited public hospital resources and the huge medical needs of patients. At the same time, due to imperfect top-level design, medical insurance network, and hierarchical diagnosis and treatment system, high-quality medical resources are occupied by "minor diseases" on the one hand, and primary medical resources have been idle for a long time on the other. In order to solve the difficult problem of poor drinking and expensive medical treatment, countries around the world have invested huge financial resources in medical construction, aiming to improve the utilization rate of medical resources and overcome the uneven distribution of medical resources...

AI Technical Summary

Problems solved by technology

[0004] In practical applications, at present, the business model of the Internet medical industry is not clear. To manage medical big data resources and build medical big data services, several problems must be solved. For example, software applications in the medical field are based on different software and hardware. The platform has extensive heterogeneity in the underlying technology and business processes, making it very difficult to achieve data sharing among different medical user groups (such as electronic medical records, medical images, etc.)

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