Abstract
Any health care system will be effective only if relevant patient information is available to make specific diagnosis. Many health centers employ different strategies to collect the medical history of patients, of which face-to-face interaction is the common technique. But in most of the cases, the concerned medical staff is not able to collect relevant medical history of a patient and this may affect the process of further medical analysis of the patient. This paper proposes semantic analysis and prediction of various risks in Diabetic patients. We have used ontology driven approach to perform the analysis and to predict the risk. We assess the diabetic patient risk factors due to smoking, alcohol intake, erectile dysfunction, and cardiovascular problems. According to the patient history, a total score is calculated for each of the above factors. According to the score, the ontology performs the risk assessment on a patient profile and predicts the potential risks and complications of the patient.
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P.C., S., P.V., V., Krishnan, R., Takroni, Y. (2014). Semantic Analysis and Prediction of Various Risks of Diabetic Patients. In: Klinov, P., Mouromtsev, D. (eds) Knowledge Engineering and the Semantic Web. KESW 2014. Communications in Computer and Information Science, vol 468. Springer, Cham. https://doi.org/10.1007/978-3-319-11716-4_10
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DOI: https://doi.org/10.1007/978-3-319-11716-4_10
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-11715-7
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