Transactions on Mass-Data Analysis of Images and Signals
P-ISSN1868-6451, E-ISSN 2509-9353

Volume 10 - Number 1 - September 2019 - Page 3-18

Modeling the Risks of Telemedicine Diagnosis

Calin Cuifudean

"Stefan cel Mare" University, Romania


For medical specialists prevention is always preferred to treatment, especially when access to patient is difficult and in emergency cases it is mandatory to have a specialized intervention by distance, i.e. one may need a telemedicine facility. In order to prevent and to intervene using telemedicine staff we need good logistics, both for data transmission and good prediction tools. Our paper deals with telemedicine`s availability diagnosis by using discrete event models. Physicians’ expertise in medical examination and laboratory analysis are here modeled using Markov chains and their dynamics on medical diagnosis and treatment is estimated. As Petri nets (PN) and Markov chains are well established formalisms for modeling and representing knowledge dynamics we use them for improving the state of the art in epidemic casualty’s models by means of risk estimation availability, interoperability, and prevention, e.g. medical diagnosis, throughout tele-medical techniques. An example will emphasize our approach.

Keywords: Telemedicine, Markov Chains, Medical Diagnosis Risks, Rare Events, Discrete Event Systems

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