Keke Gai, Meikang Qiu, Saravanan Jayaraman, Lixin Tao
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Ontology-Based Knowledge Representation for Secure Self-Diagnosis in Patient-Centered Teleheath with Cloud Systems
The implementation of cloud computing in tele-health has enabled enormous benefits of improving health-care services as well as active health approaches, such as Patient-Centered Telehealth (PCT). Applying cloud systems enables healthcare users to obtain medical information from multiple cloud-based platforms or sources. Various service deployments meet different customers' needs. As one of the popular information sharing manners on clouds, Online Self-Diagnosis (OSD) has been widely implemented for recommending medicines or treatment plans in the varied medical fields. However, there is a great risk for users when executing OSD since lack of professional pharmacological knowledge. This paper concentrates on this issue and proposes an ontology-based approach representing the medical knowledge for alarming potential risks. The proposed mechanism is named Secure Ontology-based Self-diagnosis (SOS) Model that is designed to generate knowledge of medical treatments or incompatibility of medicines to avoid improper behaviors of diagnoses. Based on the proposed model, our algorithm uses structure-level technique applying semantic schemas, which is Propositional Satisfiability Matching Algorithm (PSMA). Our experiment has proved the feasibility of our proposed mechanism.