Title :
A Survey on Data-Mining Technologies for Prediction and Diagnosis of Diabetes
Author :
Shivakumar, B.L. ; Alby, S.
Author_Institution :
Sri Ramakrishna Eng. Coll., Coimbtaore, India
Abstract :
The recent report of WHO shows a remarkable hike in the number of diabetic patients and this will be in the same pattern in the coming decades also. Early identification of diabetes is an important challenge. Data mining has played an important role in diabetes research. Data mining would be a valuable asset for diabetes researchers because it can unearth hidden knowledge from a huge amount of diabetes-related data. Various data mining techniques help diabetes research and ultimately improve the quality of health care for diabetes patients. This paper provides a survey of data mining methods that have been commonly applied to Diabetes data analysis and prediction of the disease.
Keywords :
data analysis; data mining; diseases; medical computing; patient diagnosis; research and development; WHO; data-mining technologies; diabetes data analysis; diabetes diagnosis; diabetes prediction; diabetes research; diabetes researchers; disease prediction; Association rules; Decision trees; Diabetes; Diseases; Insulin; Plasmas;
Conference_Titel :
Intelligent Computing Applications (ICICA), 2014 International Conference on
Conference_Location :
Coimbatore
DOI :
10.1109/ICICA.2014.44