The future of health care may be in “predictive health” that emphasizes prediction instead of diagnosis. Nowadays, the researchers are mining the data provided in social networks, aiming in prediction of diverse phenomena like social, political, medical, etc. The first part of the paper outlines the e-Health revolution phenomena. Next, we are focused on proposing a searching algorithm for predicting children general diseases in FYROM. The prediction task of the health related issues of specific people from noisy data is taken into consideration. We offer a model that can predict children general diseases with high percentage precision and good semantic recall on the basis of special designed ontology and social ties with other people, as revealed by their posts in social networks which is advised to be used by young mothers in our country. Also the architecture for ontology to database conversion is suggested and ready for implementation
