Clinical Decision Support System is a set of rules derived from the medical professionals applied on dynamic knowledge. Data mining is suitable to support decision-making in the healthcare industry. There are several classification techniques available that can be used for clinical decision support systems. Different techniques are used for different diagnosis. To resolve this problem, we propose the use of a phased approach to diagnosis. In this research, ontology classifications of skin diseases like chronic dermatitis, Pityriasis Rubra Pilaris, Seborrheic Dermatitis, Psoriasis, Lichen Planus, based on symptoms and other vital signs of patients were studied using an improved SVM for its diagnosis. Improved SVM based classification is used for an accurate and fast machine learning algorithm while Ontology is widely used for knowledge-based information grouping and structuring. The training data based on various characteristics of the skin disease were passed onto an Improved SVM for Classification. The results obtained by this method were helpful for the diagnosis, support and accurate information about the disease.
Volume 11 | 08-Special Issue
Pages: 2203-2208