A Distributed and Collaborative Intelligent System for Medical Diagnosis

  • Naoufel Khayati
    High School of Engineers of Sousse, University of Sousse naoufel.khayati[at]soie.rnu.tn
  • Wided Lejouad-Chaari
    SOIE Laboratory (Optimization Strategies and Intelligent Computing), University of Tunis


In this paper, we present a distributed collaborative system assisting physicians in diagnosis when processing medical images. This is a Web-based solution since the different participants and resources are on various sites. It is collaborative because these participants (physicians, radiologists, knowledgebasesdesigners, program developers for medical image processing, etc.) can work collaboratively to enhance the quality of programs and then the quality of the diagnosis results. It is intelligent since it is a knowledge-based system including, but not only, a knowledge base, an inference engine said supervision engine and ontologies. The current work deals with the osteoporosis detection in bone radiographies. We rely on program supervision techniques that aim to automatically plan and control complex software usage. Our main contribution is to allow physicians, who are not experts in computing, to benefit from technological advances made by experts in image processing, and then to efficiently use various osteoporosis detection programs in a distributed environment.
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Khayati, N., & Lejouad-Chaari, W. (2013). A Distributed and Collaborative Intelligent System for Medical Diagnosis. ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal, 2(2), 1–16. https://doi.org/10.14201/ADCAIJ201325116


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