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  1. University of Computer Studies, Yangon
  2. Conferences

Enhancement of Diagnosis System for Tuberculosis Using Case-based Reasoning

http://hdl.handle.net/20.500.12678/0000003763
http://hdl.handle.net/20.500.12678/0000003763
fa018b4e-b128-48af-ab7b-24b3d06bf2e8
d207e3fa-2e2c-41dc-9bcf-841bbdb5c96d
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Publication
Title
Title Enhancement of Diagnosis System for Tuberculosis Using Case-based Reasoning
Language en
Publication date 2009-12-30
Authors
Cing, Dim Lam
Thwin, Khin Lay
Description
Case-based Reasoning (CBR) is a recent approach to problem solving and learning that has got a lot of attention over the last few years. CBR is an Artificial Intelligence method based on a plausible cognitive model of human reasoning. People take a great interest in computer and then computer-based methods are increasingly used to improve the quality of the medical services. CBR is considered established method for building medical diagnosis systems. Traditional expert systems model human problem solving as a deductive process. They construct a solution by applying general rules to the description of a problem. It becomes apparent that human experts rely heavily on memory of past cases when solving problems. In this paper, a system is presented using CBR and decision tree algorithm for medical diagnosis. It is implemented for the efficient diagnosis of tuberculosis. This system is proposed as a development tool. The main feature of the proposed system is to provide a simple and integrated tool for designing diagnostic applications. This system also provides for helping the Tuberculosis disease and controlling the treatments for patients. So that, every user can do the diagnosis as a physician.
Keywords
Case-Based Reasoning, Decision Tree Algorithm
Identifier http://onlineresource.ucsy.edu.mm/handle/123456789/1496
Journal articles
Fourth Local Conference on Parallel and Soft Computing
Conference papers
Books/reports/chapters
Thesis/dissertations
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