Mining Based Decision Support Multi-agent System for Personalized e-Healthcare Service
In this paper, we proposed a multi-agent based healthcare system (MAHS) which is the combination of a medical sensor module and wireless communication technology. This MAHS provides broad services for mobile telemedicine, patient monitoring, emergency management, doctor’s diagnosis and prescription, patients and doctors and information exchange between hospital workers over a wide area. Futher more, MAHS is connected to a Body Area Network (BAN) and a doctor and hospital support staff. In this paper, we demonstrate how we can collect diagnosis patterns, classify them into normal, and emergency and be ready for an emergency by using the real-time biosignal data obtained from a patient’s body. This proposed method deals with the enormous quantity of real-time sensing data and performs analysis and comparison between the data of patient’s history and the real-time sensory data. In this paper, we separate Association rule exploration into two data groups: one is the existing enormous quantity of medical history data. The other group is real-time sensory data which is collected from sensors measuring body temperature, blood pressure, pulse. We suggest methods to analyze and model patterns of a patient’s state for normal, and very emergency, and making decisions about a patient’s present status by utilizing these two data groups.
KeywordsHealthcare System Multi-Agent System Ubiquitous Computing Environment Mining Association Rule
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