Medical cloud platform data sharing system and method based on third-party business

A system for sharing data on a medical cloud platform based on third-party business, comprising:

• a terminal device and a cloud platform;
• the cloud platform comprises:
• a cloud-platform data communication subsystem, a cloud-platform data support subsystem and a cloud-platform third-party-business subsystem;
• wherein the cloud-platform data communication subsystem is configured for data communication between the cloud-platform third-party-business subsystem and the terminal device;
• wherein the cloud-platform data support subsystem is configured to, by applying a deep-learning framework of distributed parallel computation, process and store in real time data received by the cloud-platform;
• wherein the cloud-platform third-party-business subsystem is configured to provide third-party business according to a service requesting instruction of the terminal device, and is further configured to perform auxiliary analysis and checking of abnormal data that are processed by the cloud-platform data support subsystem;
• and
• the terminal device comprises:
• a service terminal device and a vital-sign monitoring device of ICUs, and is configured to send data to the cloud-platform according to a destination address, and receive service of the third-party business;
• wherein the data comprise:
• a service instruction and vital-sign data;
• the cloud-platform data communication subsystem comprises:
• a data communicator and a data preprocessor;
• the data communicator is configured to receive in real time data of a plurality of terminal devices, and perform data interaction with a user, send the service instruction in the data to the cloud-platform third-party-business subsystem, and transmit the vital-sign data to the data preprocessor;
• the data preprocessor is configured to bind an ID code of a vital-sign monitoring device and patient information to generate a service serial number, and simultaneously perform resolving, classification and data-format standardizing processing of the vital-sign data, reserve a device-initial-alarming-event identifier, encapsulate integrally the service serial number and the vital-sign data as preprocessed, and save the encapsulated data into a vital-sign database;
• the cloud-platform third-party-business subsystem comprises a first processor of third-party-business serving and a third-party-business terminal;
• the first processor of third-party-business serving is configured to receive the service instruction, and provide a third-party-business service to the user;
• and the third-party-business terminal is configured for the auxiliary analysis and checking of the vital-sign data of the cloud platform;
• the cloud-platform data support subsystem comprises:
• a message bus, a data storage and a second processor of real-time analyzing and processing;
• the message bus is configured to connect and control data transmission among the subsystems and the processors, the message bus, the data storage, the data communicator and the data preprocessor of the cloud platform;
• the data storage comprises the vital-sign database, a file database, a business-information database and a buffer database, and is configured for storing and invoking of the data;
• and
• the second processor of real-time analyzing and processing is configured to read in real time data in the vital-sign database, perform analysis and processing, generate a data analysis report, and send the data analysis report to the service terminal device for browsing and reading, and simultaneously save the data analysis report into the file database;
• wherein the second processor of real-time analyzing and processing is configured to perform real-time analysis and screening of the vital-sign data by using a mode of on-line real-time data analysis and processing and a deep-learning framework based on Spark engine;
• the deep-learning framework of the Spark distributed parallel computation is configured to read in real time the vital-sign data in the vital-sign database, wherein the Spark engine is configured to, according to a preset micro-batching time interval, create in parallel a plurality of tasks, and trigger a Spark Streaming to split the data by types into RDD data collections, and simultaneously control a center model of a corresponding type to calculate and process the type of data;
• and the center model is configured to, when abnormal data that exceed a preset reference are found by the calculating and processing, analyze features of the abnormal data, calculate a duration, and mark an attribute of the abnormal data;
• the second processor of real-time analyzing and processing is configured to generate a real-time-data analysis report from the abnormal data, and send an abnormal-event warning to the user;
• the second processor of real-time analyzing and processing is configured to integrate the vital-sign data of a whole process of a user that have been analyzed and screened, and generate a dynamic-data analysis report;
• and
• the second processor of real-time analyzing and processing is configured to, by using the vital-sign data that have been analyzed and screened, train and optimize in real time a center model of each type, to obtain a new center model of the type of data.