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Scholars Journal of Engineering and Technology | Volume-3 | Issue-05
Support Vector Machine Classification Using Psychological and Medical-Social Features in Patients with Fibromialgya and Arthritis
Yolanda Garcia-Chimeno, BegoƱa Garcia-Zapirain, Heather Rogers
Published: May 25, 2015 |
121
141
DOI: 10.36347/sjet
Pages: 567-571
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Abstract
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.