DocumentCode :
2403543
Title :
Prediction of heart disease medical prescription using radial basis function
Author :
Hannan, Shaikh Abdul ; Mane, A.V. ; Manza, R.R. ; Ramteke, R.J.
Author_Institution :
Dept. of Comput. Sci., Vivekanand Coll., Aurangabad, India
fYear :
2010
fDate :
28-29 Dec. 2010
Firstpage :
1
Lastpage :
6
Abstract :
Artificial Neural Network (ANN) are one of the recently explored advanced technologies which shows promise in the area of medical. In this paper, Radial Basis Function is used to predict the medical prescription of heart disease. This work includes the detailed information about the patient´s symptoms and preprocessing was done. The trainee doctors can also use this web based tool for diagnosis and appropriate medical prescription of heart disease using radial basis function. About 300 patient´s data were collected from Sahara Hospital, Aurangabad under the supervision of heart specialist. The radial basis function is applied to heart disease data for prediction of medical prescription of heart disease. Results obtained show that radial basis function can be successfully used for prescribing the medicines for heart disease. The role of effective diagnosis and the advantages of data training on neural networks-based automatic medical diagnosis system are suggested by the outcomes.
Keywords :
Web services; cardiology; diseases; patient diagnosis; radial basis function networks; artificial neural network; automatic medical diagnosis; heart disease; medical prescription; patient symptoms; radial basis function; web based tool; Artificial neural networks; Diseases; Electrocardiography; Heart; History; Medical diagnostic imaging; Heart disease; Medical Diagnosis; Radial Basis Function;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computational Intelligence and Computing Research (ICCIC), 2010 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4244-5965-0
Electronic_ISBN :
978-1-4244-5967-4
Type :
conf
DOI :
10.1109/ICCIC.2010.5705900
Filename :
5705900
Link To Document :
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