Earticle

초록

영어

In this paper, we present a work consisting of conceiving and realizing a decision making support system for the clinical decision. Being based on Case-Based Reasoning (CBR) the system will highlight the impact of this technique in the clinical decision making domain. The experience has its importance in medicine, and the nature of CBR has motivated us to use it for the diagnosis and the therapy of a very grave respiratory disease bound to tobacco, for instance the Chronic Obstructive Pulmonary Disease (COPD). Our approach proposes to apply a CBR process by modeling the adaptation phase with an independent component: an expert system using forward chaining. For the retrieval phase, some heuristics have been traced for estimating the similarity on missing data and symbolic descriptors. Preliminary experimentations show that the expert system models well the adaptation task and gives satisfactory answers to the user. For the retrieval phase, our heuristic functions have proved a good impact on the results.

목차

Abstract
 1. Introduction
 2. Case-Based Reasoning
  2.1. CBR Process
  2.2. CBR in Medicine
 3. Related Works
 4. The Proposed Model
  4.1. Field of Application: COPD
  4.2. Architecture of the Proposed Model
  4.3. Case Representation
  4.4. Retrieval Phase
  4.5. Reuse Phase by RBR Module
  4.6. Revise and Retain Phases
 5. Implementation and Results
  5.1. Missing Data
  5.2. Symbolic Descriptors
  5.3. Reuse Phase by RBR Module
 6. Conclusion
 References

키워드

저자

• Souad Guessoum [ LRS Laboratory ]
• M.Tayeb Laskri [ LRI Laboratory ]
• Hayet djellali [ LRS Laboratory ]
• M. Tarek Khadir [ LabGed Laboratory ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Hybrid Information Technology

• 간기

  격월간

• pISSN

  1738-9968

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605