Title :
Mining medical data to identify frequent diseases using Apriori algorithm
Author :
Ilayaraja, M. ; Meyyappan, T.
Author_Institution :
Dept. of Comput. Sci. & Eng., Alagappa Univ., Karaikudi, India
Abstract :
The data mining is a process of analyzing a huge data from different perspectives and summarizing it into useful information. The information can be converted into knowledge about historical patterns and future trends. Data mining plays a significant role in the field of information technology. Health care industry today generates large amounts of complex data about patients, hospitals resources, diseases, diagnosis methods, electronic patients records, etc,. The data mining techniques are very useful to make medicinal decisions in curing diseases. The healthcare industry collects huge amount of healthcare data which, unfortunately, are not “mined” to discover hidden information for effective decision making. The discovered knowledge can be used by the healthcare administrators to improve the quality of service. In this paper, authors developed a method to identify frequency of diseases in particular geographical area at given time period with the aid of association rule based Apriori data mining technique.
Keywords :
data mining; diseases; health care; medical administrative data processing; Apriori algorithm; association rule; decision making; diagnosis method data; disease identification; electronic patients record; health care administrator; health care industry; hospitals resource data; information technology; medical data mining; medicinal decision; patient data; quality of service; Association rules; Diseases; Heart; Itemsets; Liver; Medical diagnostic imaging; Apriori Algorithm; Association Rule; Data Mining; Frequent Diseases; Medical Data;
Conference_Titel :
Pattern Recognition, Informatics and Mobile Engineering (PRIME), 2013 International Conference on
Conference_Location :
Salem
Print_ISBN :
978-1-4673-5843-9
DOI :
10.1109/ICPRIME.2013.6496471