Abstract
Case-based reasoning (CBR) is an appropriate methodology that applies logical reasoning using similarity measure to relate a current problem case with past similar cases. It has been applied successfully in medical diagnosis and has been experimented in different domains of application in diagnosis and detection. In this paper, we have proposed knowledge-based decision support system which uses the concept of CBR to detect cholera disease. CBR is problem solving method which is derived from artificial intelligence and is based on some base cases which can be revised in order to determine homogeneous cases for new problem. Experimental results show that the proposed model Cholera Easy Detection System (CEDS) assists the doctors to make a consistent decision. Through this work, we are intending to provide facility to the medical research scholars as well as medical unit in order to help them identify cholera when the patient is infected with correspondence symptoms of that disease. Moreover, the CEDS also assists in minimizing errors of deviation that have been found to be noticeable cause of medical errors.
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Acknowledgment
The authors express deep sense of gratitude to the JNM Hospital, Kalyani, West Bengal, India, for contributing their valuable advices and to the Dept. of Engineering and Technological studies where the actual work has been carried out.
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Chakraborty, S., Pal, C., Chatterjee, S., Chakraborty, B., Ghoshal, N. (2015). Knowledge-Based System Architecture on CBR for Detection of Cholera Disease. In: Mandal, D., Kar, R., Das, S., Panigrahi, B. (eds) Intelligent Computing and Applications. Advances in Intelligent Systems and Computing, vol 343. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2268-2_17
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DOI: https://doi.org/10.1007/978-81-322-2268-2_17
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