Abstract
Chronic diseases such as cancer, stroke, hypertension, coronary heart disease, and diabetes seriously harm human health. According to the statistics of the World Health Organization (WHO), cancer is the leading cause of death in the world, and constitutes a great public health challenge for all the countries worldwide. To optimize the chronic prevention and control model, it is inevitable to strengthen the analysis of multi dimension data including multi omics’ screening, physical examination, health condition and lifestyle data, to evaluate and identify high-risk groups effectively, and reduce the chronic disease risk through accurate, appropriate and effective intervention methods. In this paper, integrating genetic testing, physical examination, diet style, habits and customs, medical history, and exercise data together, we design and implement a personalized nutrition service that calculates the disease risk and nutrition requirement and then provides a tailored nutrition solution to reduce the risk of suffering from chronic diseases and the risk of death from chronic diseases.
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Acknowledgment
This research project is supported by Science Foundation of Beijing Language and Culture University (supported by “the Fundamental Research Funds for the Central Universities”) (Approval number: 22YJ080008).
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Yang, J. (2022). Tailored Nutrition Service to Reduce the Risk of Chronic Diseases. In: Traina, A., Wang, H., Zhang, Y., Siuly, S., Zhou, R., Chen, L. (eds) Health Information Science. HIS 2022. Lecture Notes in Computer Science, vol 13705. Springer, Cham. https://doi.org/10.1007/978-3-031-20627-6_7
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DOI: https://doi.org/10.1007/978-3-031-20627-6_7
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