Medical cloud system, method and system for medical big data processing and medium

Abstract

The invention provides a medical cloud system, method and system for medical big data processing and a medim. IT resources of a hospital are pooled through a virtualization technology, on the basis ofhospital private cloud, a virtual desktop architecture is adopted to be upgraded into medical community cloud, and through a medical big data processing system based on Hadoop, a distributed computing mode is used for solving the problems of medical big data collection, storage and analysis. An Apriori algorithm oriented to the medical big data in a cloud environment is provided, a transaction database is converted into a Boolean matrix by utilizing a matrix thought, a transaction storage mode and matrix rows and columns are compressed and improved, algorithm end conditions are optimized, andthe data is transplanted to a Hadoop medical big data platform to realize MapReduce parallel processing. According to the method, the database scanning frequency is effectively reduced, and the problems of algorithm serialization, low efficiency of generating frequent item sets and the like are solved.

Description

technical field [0001] The field of computer data processing technology involved in this application, in particular, relates to a medical cloud system, method, system and medium for medical big data processing. Background technique [0002] With the rapid development of information technology, especially the rise of cloud computing and big data-related technologies in recent years, more and more domestic medical institutions have begun to accelerate the change of the traditional model of hospital informatization, and realize the transformation and upgrading of digital hospital construction to improve Its own medical service level and core competitiveness. Based on the medical cloud service model of cloud computing, a new type of digital hospital information platform architecture system is established, so that medical institutions can use the medical cloud platform to improve "patient-centered" clinical medical services and meet the needs of medical resource radiation. Faced...

AI Technical Summary

Problems solved by technology

[0005] (1) Low utilization of hardware resources

According to statistics, the CPU utilization rate of servers in general hospitals is basically less than 5%, and the storage utilization rate is about 30%. There is a serious waste of hardware resources.

[0006] (2) Uneven resource redundancy scheduling

In order to ensure the business continuity of the hospital's core business system, the hospital generally provides a high-availability dual-machine hot standby mode, but only one set of machines is providing services, and the other set is idle for a long time

[0007] (3) The operation of the business system is not safe

Since most of the business systems are only installed on one server, there is a single point of failure. Once the business is interrupted due to downtime, the provision of 7*24 hours of medical services cannot be guaranteed

[0008] (4) Data is isolated and not shared

[0009] (5) IT construction is not environmentally friendly

Each business system relies on one or more physical servers, which not only consumes power for the server itself, but also increases the energy consumption of other auxiliary equipment in the computer room, such as refrigeration equipment

[0010] (6) The operation and maintenance management platform is not unified

[0012] Under the traditional IT architecture model, deploying medical information systems to realize hospital information construction is a very expensive and complicated project

Compared with large medical institutions, grassroots medical institutions face huge problems when implementing hospital informatization construction: due to the uneven distribution of medical resources in my country and the lack of resources in grassroots medical institutions, investment in hospital informatization construction faces serious shortage of funds and investment The problem of low return rate; due to the shortage of medical informatization talents in my country, the IT departments of grassroots medical institutions are weak, unable to undertake the tasks of hospital information system construction, maintenance, management and upgrading; Lack of maintenance and updates leads to poor user experience, and medical workers will resist the development of information technology

From the perspective of the distribution of medical resources in my country, the distribution between regions and hospitals is extremely unbalanced, most of the medical investment is concentrated among large hospitals, and the grassroots hospitals that also shoulder the heavy responsibility of serving patients do not have enough funds to build Its own medical information system does not have enough professionals with professional IT literacy to manage and maintain it

Finally, the distribution and utilization of clinical business data is unreasonable

Unreasonable hospital information system architecture and unreasonable distribution of medical resources also lead to non-sharing and non-centralization of clinical business data, which will lead to the failure of reasonable and effective use of clinical business data with great medical value

Today, with the arrival of the era of big data, these unreasonable factors have caused the secondary utilization of medical big data to fall into a huge dilemma.

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