AI Article Synopsis
- Asthma impacts about 7% of the French population, leading to significant health challenges, and a decision support system is proposed to help manage this chronic condition effectively.
- The development of this system, ADEMA, utilized the Case-Based Reasoning approach and involved analyzing asthma consultation data from the RESALIS health care network to create a case model.
- A similarity metric based on the MVDM method was employed, and two methods were created for reusing similar cases, with an evaluation of ADEMA's effectiveness included.
Article Abstract
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 Fedialis 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 case model for our system. Our similarity metric is based on the MVDM method. We developed two methods to reuse retrieved cases. We present our data analysis results and similarity metric from which we designed our Case Based System for asthmatic patients health care: ADEMA. To conclude, an evaluation of ADEMA is presented.
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