Contribution Title a Correlational Diagnosis Prediction Model for Detecting Concurrent Occurrence of Clinical Features of Chikungunya and Zika in Dengue Infected Patient

Vector-Bonne diseases are major challenges in the society worldwide. Every country is suffering from vector borne disease every year. This study is conducted to detect concurrent occurrence of clinical features of Chikungunya and Zika in Dengue infected Patient. This paper has proposed correlational Diagnosis Prediction Model for detecting Concurrent occurrence of Clinical Features of Chikungunya and Zika in Dengue infected Patient. In this propose model, patient data is evaluated with the help of propose diagnosis algorithm for predicting these diseases. An experimental environment is setup for evaluating the performance of propose model. The future scope of this research can be used for curing other Vector Borne Diseases.