Support Vector Machine Classification Using Psychological and Medical-Social Features in Patients with Fibromialgya and Arthritis
نویسندگان
چکیده
The SVM classifier is a very powerful tool for helping to diagnose illnesses. Subjects can be classified according to certain characteristics related to pathology. In this paper, the aim is to undertake a classification of arthritis and fibromyalgia pathologies using medico-social and psychopathological characteristics obtained from questionnaires, with a very high classification percentage having been obtained. A 96.4035% success rate was obtained using the SVM classifier only by introducing the psychopathological characteristics. Only specific questionnaires could be put together and the subject diagnosed if they have either fibromyalgia or arthritis, whereby the cost of tests that these types of pathology entail might be considerably reduced.
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