Paper Title
Implementation Of Svm And Nb Algorithms For Classification Of Diseases And Their Treatments

Now days, the standard healthcare system mainly depends on the delivery of modern and efficient healthcare services. Due to time and cost constraints, most of the people rely on healthcare system to obtain healthcare services. Healthcare system becomes very important to develop an automated tool that is capable of identifying and discriminating relevant healthcare information. This will not only help common person but also to doctors to update their knowledge and have correct treatment of diseases. The medical field is one of the field in which new research is carried out at a faster rate. In a medical field automation is gaining momentum. From the medical data useful information can be extracted and made useful for generating software’s or MEDLINE applications that can help doctors in the treatment. In this paper, we have to identify diseases and their treatments in short text using SVM and NB classification algorithms. Experimental results show that SVM gives better classification result than naïve bayes. These algorithms are evaluated using four criteria: Accuracy, Precision, Recall and F-measure. Index Terms — MEDLINE, SVM,NAÏVEBAYES, NLP, HEALTHCARE DATASETS, DISEASES AND TREATMENT RELATION.