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Data fusion model from coupling ontologies and clinical reports to guide medical diagnosis process
In this article, we focus on access to data that can help clinicians in the medical diagnostic process before proposing appropriate treatment. With the explosion of medical knowledge, we are interested to structure them into the informations collection step. We propose an ontology resulting from a fusion of several existing and open medical ontologies and terminologies. On the other hand, we exploit real cases of patients to improve the list of signs of each disease. This work leads to a knowledge base (KB) associating all human diseases with their relevant signs. Cases are also stored in the KB. Each disease is described by all the signs observed and verified in all the patients carrying this same disease. The association of sickness and its signs is thus continuously nourished as there are new cases of diagnosis.