Identifying Disease -Treatment Relations Using Machine Learning Approach

Identifying the disease treatment relation enables to find what disease a person suffers from and what appropriate treatment can be given to that person. The semantic relation tags namely Cure, Prevent and Sideeffects helps to find out the relationship between disease and treatment. Many methodologies like co-occurrence analysis, rule based methodologies and statistical methods are used in disease treatment relation. However, machine learning is widely used in many applications like protein-protein interaction, extraction of medical knowledge and in health care field. we propose a machine learning approach termed as SMO classification, which uses several features namely medical papers, medical abstracts. Our approach identifies the features namely disease-treat, cure, prevent and sideeffects. The performance can be measured by Accuracy, Precision, F-measure and Recall.