Lung cancer screening system based on big data

Abstract

The invention relates to the technical field of lung cancer tumor screening and particularly relates to a lung cancer screening system based on big data. The system comprises a central server, networknodes connected with the central server through a network, and portable monitoring devices in network connection with the central server, wherein each network node is connected with a hospital data platform in an area, the hospital data platform transmits the diagnosis information of a patient to the central server in real time through the network nodes, and the portable monitoring devices are worn on bodies of patients and arranged around the patients. The system is advantaged in that preliminary screening of lung cancer can be performed on a large number of users in the earlier stage, high-risk users are reminded to go to a hospital for definite diagnosis, on one hand, a lung cancer screening range is expanded, on the other hand, cost is saved through grading screening, so medical resources are used more effectively, moreover, canceration possibility prediction is carried out on the patients suffering from lung diseases, and lung cancer is restrained in the early stage of cancer intime.

Description

technical field [0001] The invention relates to the technical field of lung cancer screening, in particular to a big data-based lung cancer screening system. Background technique [0002] At present, with the rapid development of Internet technology and the advancement of big data technology, some lung cancer databases have been built in my country, and such databases are scattered in a very small number of teaching hospitals and central hospitals. However, major hospitals use their own medical systems, and the same patient data adopts different recording rules, resulting in the inability to integrate lung cancer patient information. Because of the differences in the electronic medical record systems used by each hospital, tumor patient data cannot be collected and used uniformly. Patient data is just a decoration, and there is a phenomenon of "rich data that cannot be unified". Therefore, how to make full use of these valuable information resources to provide scientific gu...

AI Technical Summary

Problems solved by technology

However, major hospitals use their own medical systems, and the same patient data adopts different recording rules, resulting in the inability to integrate lung cancer patient information. Because of the differences in the electronic medical record systems used by each hospital, tumor patient data cannot be collected and used uniformly. Patient data is just a decoration, and there is a phenomenon of "rich data that cannot be unified"

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