Data Analysis of Medical Records in Veterinary Hospital Using Clustering Method and Association Rule

Authors

Tsung-Chih Hsiao, College of Computer Science and Technology, Huaqiao University, China.Follow
Shu-Ling Shieh, Department of Information Networking and System Administration, Ling Tung University, Taiwan.Follow
Tzer-Long Chen, Department of Creative Product Design, Ling Tung University, Taiwan.Follow
Chia-Hui Liu, Department of Digital Literature and Arts, St. John’s University, Taiwan.Follow
Ying-Chi Yeh, The Graduate Institute of Applied Information Technology, Ling Tung University, Taiwan.Follow

Author Country (or Countries)

Taiwan.

Abstract

Since pets have been promoted from working livestock to family companions, pet industry is also progressing with the development of nowadays? society. To reduce the negligence of the diagnostic process, the correlations between the symptoms and treatments of sick pets are collected. Medical records of a veterinary hospital are used as the input dataset. The clustering algorithms and association rules use two methods to investigate the practice. The result indicates that urology, dermatology or internal medicines are highly correlated with possible symptoms. The conclusion could assist doctors to find the association rules between diseases and symptoms of pets. In this paper, the medical records of pets are analyzed using the data mining method of Clustering Algorithm based on Histogram Threshold (HTCA). HTCA is composed of hierarchical clustering method and Otsu?s method. Two steps are applied in the experiments. First, we find the proper clustering by applying HTCA clustering method, and then apply the association rule to find the impact of divisions of property. Experiment shows that, the attributes of impacting factors and to efficiently find medical records in veterinary hospitals.

Recommended Citation

Hsiao, Tsung-Chih; Shieh, Shu-Ling; Chen, Tzer-Long; Liu, Chia-Hui; and Yeh, Ying-Chi (2015) "Data Analysis of Medical Records in Veterinary Hospital Using Clustering Method and Association Rule," Applied Mathematics & Information Sciences: Vol. 09: Iss. 6, Article 59.
Available at: https://digitalcommons.aaru.edu.jo/amis/vol09/iss6/59