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Title:
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USING SOCIAL MEDIA TO PREDICT CHILDREN DISEASE OCCURRENCE |
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Author(s):
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Marika Apostolova Trpkovska, Betim Cico, Ivan Chorbev |
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ISBN:
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978-989-8704-04-7 |
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Editors:
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Philip Powell, Miguel Baptista Nunes and Pedro Isaías |
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Year:
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2014 |
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Edition:
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Single |
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Keywords:
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Children disease prediction algorithm; ontology/database conversion architecture; semantic web; social network. |
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Type:
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Full Paper |
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First Page:
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209 |
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Last Page:
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216 |
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Language:
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English |
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Cover:
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Full Contents:
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click to dowload 
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Paper Abstract:
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Delivering care in the future may focus on predicting health needs rather than waiting for disease to begin. So, the future of health care may be in predictive health that emphasizes as much as possible prediction and as less as possible diagnoses that are coming from these predictions. Nowadays, the researchers are mining the data provided in social networks, aiming in prediction of diverse phenomena like social, political, medical, etc. We are focused on proposing a model for predicting children general diseases. 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. This model is a part of the specially designed social network where the patient medical data are not included concerning their privacy and sensitivity. Through the social network we a giving the possibility to mothers to exchange their experiences through different social services. And through the proposed disease prediction model we a giving the possibility to mothers to gain some preliminary predicted diagnosis, if needed. |
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