Research and Application of Data Mining in Chronic Diseases
- Yuliang Shi, Jun Tao
- Corresponding Author
- Yuliang Shi
Available Online March 2018.
- https://doi.org/10.2991/mecae-18.2018.39How to use a DOI?
- Apriori algorithm, data mining, association rules.
- In recent years, with the acceleration of people's pace of life, the number of chronic diseases in China is increasing. The attention and investment of the country to the medical industry is increasing year by year. At the same time, with the maturity and perfection of data mining technology, many countries have applied this technology to the research and mining of medical data. In this paper, the Apriori algorithm of data mining technology, and improve the data format of the Apriori algorithm is applied to the prediction of nephropathy, establish the association rules between chronic disease and a number of physical data by the algorithm, and the experimental results proved that Apriori algorithm is effective in the medical data mining.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yuliang Shi AU - Jun Tao PY - 2018/03 DA - 2018/03 TI - Research and Application of Data Mining in Chronic Diseases BT - 2018 International Conference on Mechanical, Electronic, Control and Automation Engineering (MECAE 2018) PB - Atlantis Press SN - 2352-5401 UR - https://doi.org/10.2991/mecae-18.2018.39 DO - https://doi.org/10.2991/mecae-18.2018.39 ID - Shi2018/03 ER -