RespiDiag: a Case-Based Reasoning System for the Diagnosis of Chronic Obstructive Pulmonary Disease

Souad Guessoum 1, * Mohamed Tayeb Laskri 1 Jean Lieber 2
* Auteur correspondant
2 ORPAILLEUR - Knowledge representation, reasonning
Inria Nancy - Grand Est, LORIA - NLPKD - Department of Natural Language Processing & Knowledge Discovery
Abstract : In this paper a decision support system for the diagnosis of a very serious respiratory disease caused by tobacco and named the chronic obstructive pulmonary disease is presented. The system is based on case-based reasoning principles and gathers the experience of experts of the pneumology department of Dorban Hospital (Annaba, Algeria). A critical issue about the case base is that some values of the features are missing in most cases. Five approaches for managing this problem of missing data are proposed. Three of them allow evaluating the similarity despite the missing information. The two other approaches are proposed for filling the voids by plausible values using a statistical method and the principle of case-based reasoning itself.
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Article dans une revue
Expert Systems with Applications, Elsevier, 2014, 41 (2), pp. 267--273. 〈http://www.sciencedirect.com/science/article/pii/S0957417413003631〉. 〈10.1016/j.eswa.2013.05.065〉
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https://hal.inria.fr/hal-00912641
Contributeur : Jean Lieber <>
Soumis le : lundi 2 décembre 2013 - 14:24:12
Dernière modification le : dimanche 8 avril 2018 - 11:48:13

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Souad Guessoum, Mohamed Tayeb Laskri, Jean Lieber. RespiDiag: a Case-Based Reasoning System for the Diagnosis of Chronic Obstructive Pulmonary Disease. Expert Systems with Applications, Elsevier, 2014, 41 (2), pp. 267--273. 〈http://www.sciencedirect.com/science/article/pii/S0957417413003631〉. 〈10.1016/j.eswa.2013.05.065〉. 〈hal-00912641〉

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