Symptoms - Diagnostic System using Artificial Neural Networks in a Web Environment 


Vol. 9,  No. 4, pp. 407-414, Aug.  2002
10.3745/KIPSTB.2002.9.4.407


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  Abstract

Being recently increased interests of our healthcare, a host of symptoms-diagnostic sites has been introduced on the World Wide Web. But conventional healthcare sites provide users with only a very restricted functions. In this paper, we propose the use of Artificial Neural Networks (ANNs) as a flexible symptoms-diagnostic tool that enables learning effects of ANNs (not expert´s knowledge) to be incorporated into the diagnostic process. We develop a novel algorithm for predicting patient´s disease that satisfy user (or expert)-specified symptoms on WWW. Our algorithm provides two important benefits : 1) enables users (patients) to be taken early diagnostic, and 2) enables experts to perform confidently diagnostic by referencing the predicted diseases-list with its respective possibility.

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[IEEE Style]

S. K. Kim and B. C. Kim, "Symptoms - Diagnostic System using Artificial Neural Networks in a Web Environment," The KIPS Transactions:PartB , vol. 9, no. 4, pp. 407-414, 2002. DOI: 10.3745/KIPSTB.2002.9.4.407.

[ACM Style]

Sam Keun Kim and Byung Cheon Kim. 2002. Symptoms - Diagnostic System using Artificial Neural Networks in a Web Environment. The KIPS Transactions:PartB , 9, 4, (2002), 407-414. DOI: 10.3745/KIPSTB.2002.9.4.407.

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