ADEMA : A System to Help Physicians in the Asthma Health Care

Icham Sefion, Abdel Ennaji, and Marc Gailhardou

Asthma is a distressing disease, affecting up to 7% of the French population and causing considerable morbidity and mortality. A medical decision support system such can help physicians to control this chronic disease. Thanks to the health care network (RESALIS) of Alliance Médica (disease management branch from GlaxoSmithKline), asthma consultation data were collected to exploit them. We chose Case-Based Reasoning paradigm to develop our medical decision support system. Intelligent data analysis methods have been used to determine the knowledge models for our system. A Self-Organising Map has been used to analyse medical data to show if homogeneous groups of cases exist. A case is an asthma consultation. Our similarity metric is based on MVDM method. We present our data analysis results and similarity metric from which we designed our Decision Support System for asthmatic patients health care : ADEMA. An evaluation of ADEMA is presented.

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