TY - GEN
T1 - Research on Correlation Model of Diabetes Complications Based on CI-Apriori Algorithm
AU - Guo, Yanan
AU - Guo, Shuli
AU - Han, Lina
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - In recent years, the rapid development of computer technology has made great progress in the field of smart health-care. Using data mining technology can obtain useful information in medical big data, discover the correlations among diseases and achieve the prevention and control of diseases. However, the traditional mining algorithms can no longer satisfy the demands of medical big data, it is an important direction of future research to improve and optimize the algorithms to make them applicable to the medical field. Based on this, this paper improves Apriori algorithm through parallel processing, matrix compression, and the introduction of lifting rate and interest. The optimized algorithm is called CI-Apriori, and an association rule model of diabetes complications based on CI-Apriori is proposed. The experimental results show that CI-Apriori has a great improvement in time and space efficiency, and can mine the strong association rules among diabetes complications faster and more effectively, so as to find the medical laws for the prevention and treatment of diseases.
AB - In recent years, the rapid development of computer technology has made great progress in the field of smart health-care. Using data mining technology can obtain useful information in medical big data, discover the correlations among diseases and achieve the prevention and control of diseases. However, the traditional mining algorithms can no longer satisfy the demands of medical big data, it is an important direction of future research to improve and optimize the algorithms to make them applicable to the medical field. Based on this, this paper improves Apriori algorithm through parallel processing, matrix compression, and the introduction of lifting rate and interest. The optimized algorithm is called CI-Apriori, and an association rule model of diabetes complications based on CI-Apriori is proposed. The experimental results show that CI-Apriori has a great improvement in time and space efficiency, and can mine the strong association rules among diabetes complications faster and more effectively, so as to find the medical laws for the prevention and treatment of diseases.
KW - CI-Apriori algorithm
KW - association rule model
KW - data mining
KW - diabetes complications
UR - http://www.scopus.com/inward/record.url?scp=85181832326&partnerID=8YFLogxK
U2 - 10.1109/CCDC58219.2023.10326707
DO - 10.1109/CCDC58219.2023.10326707
M3 - Conference contribution
AN - SCOPUS:85181832326
T3 - Proceedings of the 35th Chinese Control and Decision Conference, CCDC 2023
SP - 3789
EP - 3794
BT - Proceedings of the 35th Chinese Control and Decision Conference, CCDC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 35th Chinese Control and Decision Conference, CCDC 2023
Y2 - 20 May 2023 through 22 May 2023
ER -
