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Author: Lin Zhang Ping Qi Title: Research on key technologies of personalized intervention for chronic diseases based on Case-Based Reasoning 求SCI检索信息。 |
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zhangyue919
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sunshan4379: LS-EPI+1, 感谢应助! 2022-01-14 20:55:57
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可以检索到，web of science检索结果如下： Research on Key Technologies of Personalized Intervention for Chronic Diseases Based on Case-Based Reasoning 作者 Zhang, L (Zhang, Lin) 1, 2 Qi, P (Qi, Ping) 1 COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 卷2021 文献号8924293 DOI10.1155/2021/8924293 出版时间AUG 13 2021 文献类型Article 摘要 In recent years, with the acceleration of industrialization, urbanization, and aging process, the number of patients with chronic diseases in the world is increasing year by year. In China, the number of chronic diseases has increased tenfold in 10 years. The percentage of the disease burden in the whole society accounts for 79.4%. Chronic diseases have become the top killer for Chinese people's health. However, for chronic diseases, prevention is more important than treatment. It is the best way to keep healthy. Therefore, health intervention is the key to prevent chronic diseases. Especially now, with the spread of COVID-19 pandemic, reducing the times of hospital check-ups and treatments for chronic patients is practically significant for releasing the stress on medical staffs and decreasing the rate of transmission and infection of COVID-19. In this paper, case-based reasoning (CBR) technology is used to assist personalized intervention for chronic diseases, and the key technologies of personalized intervention for chronic diseases based on case-based reasoning are proposed. The case organization, case retrieval, and case retention techniques of CBR technology in chronic disease personalized intervention are designed, and the calculation of interclass dispersion is added to the distribution of feature words, which is used to describe the distribution of feature attributes in different categories of cases. It provides an effective method for the establishment of personalized intervention model for chronic disease. 作者信息 通讯作者地址 Qi, Ping (通讯作者) Tongling Univ, Inst Serv Comp, Tongling 244061, Anhui, Peoples R China 地址 1 Tongling Univ, Inst Serv Comp, Tongling 244061, Anhui, Peoples R China 2 Anhui Sanlian Univ, Inst Robot Engn, Hefei 230000, Anhui, Peoples R China 电子邮件地址qiping929@tlu.edu.cn 类别/分类 研究方向Mathematical & Computational Biology |
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