Title :
Survey on medical diagnosis using data mining techniques
Author :
Sumalatha, G. ; Muniraj, N.J.R.
Author_Institution :
Dept. of ICT, SKASC, Coimbatore, India
Abstract :
In the nonexistence of medical diagnosis substantiations, it is complicated for the expert to speak out about the grade of disease with affirmation. Generally many tests are done that involve clustering or classification of large scale data. However many tests could complicate the main diagnosis process and lead to the difficulty in obtaining the end results, particularly in the case where many tests are performed. This kind of difficulty could be resolved with the aid of machine learning techniques. In this paper survey on three different disease diagnosis are taken in to the consideration. The heart Disease, Breast Cancer Disease and the Diabetes Disease are analyzed and observed with existing works. This survey paper reveals various existing approaches that have processed for diagnosis these diseases using data mining techniques.
Keywords :
cancer; cardiology; data mining; learning (artificial intelligence); medical diagnostic computing; patient diagnosis; pattern classification; pattern clustering; breast cancer disease; data mining; diabetes disease; disease diagnosis; heart disease; large scale data classification; large scale data clustering; machine learning; medical diagnosis;
Conference_Titel :
Optical Imaging Sensor and Security (ICOSS), 2013 International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4799-0935-3
DOI :
10.1109/ICOISS.2013.6678433