Recently, the Intel Developer Forum (IDF16) keynote speech introduced Intel and Jing Century Medical Network Technology (Beijing) Co., Ltd. ("Jianglun Century"), applying Intel's open architecture front-end IoT device and after The end-to-end big data solution of the end data analysis platform, in-depth cooperation in supporting personalized health management services. The collaboration is another successful practice for Intel to accelerate the development of medical applications based on data analytics with the help of open and innovative products and open source technologies.
In order to improve medical efficiency and cope with the increasingly severe aging phenomenon and the medical challenges brought about by the huge chronic patient population, the Chinese government is actively promoting the transformation of the medical service model from “treatment centering on disease†to “health promotion centerâ€. In this process, the application of medical informatization and IoT smart devices has accumulated a large amount of personal health data inside and outside the hospital, extracted valuable information from these massive data, established relevant health and disease assessment models, and based on personal health status and Demand, providing personalized health management solutions and management services, is the future development direction of the health service industry. Big data processing and analytics are key to achieving this change.
In order to enable health management services to help users analyze and understand their own health status, potential disease risks and health trends, and develop and implement health intervention programs through intelligent management systems, Jinglun Century cooperates with Intel to utilize its open source big data analysis. Platform TAP, establishes a chronic disease risk prediction model. Through big data processing and analysis technology, help health management organizations identify demand users and provide targeted health interventions in a timely manner. At present, Jinglun Century uses TAP to process and analyze the physical examination data of nearly 310,000 people for 2 consecutive years, and initially establishes a hypertension risk prediction model to provide decision support for the implementation of personalized health management services by health management service organizations. With the enrichment of data and continuous optimization of models, the future will provide more effective decision support for personalized health management services.
"With Intel's innovative technology support, we integrate health data from different sources, use machine learning algorithms to analyze the health data of large-scale populations, and establish an evaluation model." Intel collaborates to break through the limitations of traditional data analysis tools, take full advantage of TAP's technological advantages in big data processing, and achieve healthy big data analysis that supports millions of users and even larger users in the future, simplifying the value mining from big data. The process saves development time and labor costs and enhances the personalized health management service experience based on big data."
The use of informatization, especially intelligent technology to promote the transformation of medical service model is Intel's long-term goal in the medical field. As the initiator and participant of technological change, Intel joins hands with industry-leading partners, such as Jinglun Century, in the medical ecology. The platform is built in the system, based on leading technologies including Intel Xeon processor platform, to promote high-performance computing, big data analysis, cloud computing and other innovations to help improve the information technology level in the medical field. Intel predicted in 2015 that 50% of medical services will be provided outside the hospital in 10 years. By 2020, the development of computing technology is expected to help doctors complete the main process of precision medicine within 24 hours. In the future, Intel and the ecosystem will work together to use innovative technologies to help data centers break away from the island model, effectively use massive amounts of data, accelerate medical information innovation, and build a future collaborative medical health path.
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