Volume 19 Issue 12
Dec.  2021
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LUO Yao, DENG Xue-xue, XU Xiao-ru, FANG Rong-hua. Research on the establishment of a risk prediction model for multiple chronic diseases in the elderly based on big data[J]. Chinese Journal of General Practice, 2021, 19(12): 1979-1982. doi: 10.16766/j.cnki.issn.1674-4152.002216
Citation: LUO Yao, DENG Xue-xue, XU Xiao-ru, FANG Rong-hua. Research on the establishment of a risk prediction model for multiple chronic diseases in the elderly based on big data[J]. Chinese Journal of General Practice, 2021, 19(12): 1979-1982. doi: 10.16766/j.cnki.issn.1674-4152.002216

Research on the establishment of a risk prediction model for multiple chronic diseases in the elderly based on big data

doi: 10.16766/j.cnki.issn.1674-4152.002216
Funds:

 2020YFS0151

 HXHL19021

  • Received Date: 2020-08-24
    Available Online: 2022-03-02
  • The aging of population has become a major worldwide social problem. The elderly population in China had exceeded 254 million. High morbidity and co-morbidity of chronic diseases in the elder have led to reduce quality of their life, the increase of disability rate, mortality rate and obviously increased medical expenditures, which bring heavy burden to family and society. At present, based on the application of new technologies, such as internet of things, big data and artificial intelligence in the medical industry, traditional chronic disease management will be challenged. The development of smart medicine is the strategic need of medical health reform, as well as the inevitable trend of industry innovation, and gradually becomes the source power of disease diagnosis and risk prediction. Developing accurate and effective early diagnosis and screening technology, establishing perfect disease general survey system, risk assessment and early warning system are the key points to prevent and treat chronic diseases. Foreign countries have developed disease risk assessment models for breast cancer, lung cancer, diabetes and other diseases, but these models are not fully suitable for Chinese population to carry out disease risk assessment and measurement, so it is necessary to build disease risk assessment models that are in line with the characteristics of Chinese population. How to go beyond the traditional chronic disease management system and construct the solution of precision medical decision has become a scientific problem concerned by the medical community. In the process of practicing of chronic disease management, the classification and stratification of multiple chronic disease risk factors are the core problems. Based on a large amount of collected medical data, using machine learning technology to build a prediction model for risk assessment of multiple chronic diseases in the elderly and conducts medical data mining, and to form an index evaluation system for intervention evaluation of chronic diseases in the elderly. This model will break through the difficulties and choke point of chronic disease management, and promote the prevention/intervention of chronic diseases to move forward, and achieve accurate management in the elderly.

     

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