Designing smart agent based telemedicine systems using dynamic bayesian networks: an application to kidney disease people
Abstract
Telemedicine is the delivery of health-care services, where distance is a critical factor. The use of smart agent and artificial intelligence techniques to enhance such services is proposed through a description of the needs and goals of a smart agent based telemedicine system. A real-world example is presented and the use of dynamic bayesian networks (DBN) is promoted because DBN forms a well-suited formal framework to deal with uncertainty and stochactic processes which are characteristic of the domain of telemedicine. The model given in our real-world application aims at giving a daily diagnosis on the hydration state of kidney disease people. Our experiments are under way by using data of an already existing system.