Scheduled System Maintenance:
On May 6th, single article purchases and IEEE account management will be unavailable from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). We apologize for the inconvenience.
By Topic

Case-based support for the diagnosis of Chronic Obstructive Pulmonary Disease

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Souad, G. ; LRS Lab., Badji Mokhtar Univ., Annaba, Algeria ; Tayeb, L.M.

Case-Based Reasoning (CBR) is a technique which consists of learning from past experiences. Its use is very interest in domains where experience plays an important role in the resolution of new problems, which is the case in medical diagnosis. This paper presents a decision making support system based on CBR and applied to the diagnosis of Chronic Obstructive Pulmonary Disease (COPD), a dangerous respiratory disease bound to tobacco. In medical activity, the physicians are often in situations where they have to make decision whereas they have not all necessary data then they are essentially based on their experiences to find the most probable diagnosis. Our system aims to reproduce this behavior of physicians by estimating similarity on attributes with missing data in the most important stage of CBR process consisting to retrieve the most similar case. We have proposed implemented and tested three ideas to find the real diagnosis of cases which have missing data. Some heuristics functions have been also developed for measuring similarity on attributes with symbolic nature. Preliminary experimentations of these ideas and heuristics have proved a good impact on results.

Published in:

Complex Systems (ICCS), 2012 International Conference on

Date of Conference:

5-6 Nov. 2012