An Adaptive Temporal-Causal Network Model for Stress Extinction Using Fluoxetine - Artificial Intelligence Applications and Innovations
Conference Papers Year : 2019

An Adaptive Temporal-Causal Network Model for Stress Extinction Using Fluoxetine

Abstract

In this paper, an adaptive temporal causal network model based on drug therapy named fluoxetine to decrease the stress level of post-traumatic stress disorder is presented. The stress extinction is activated by a cognitive drug therapy (here fluoxetine) that uses continuous usage of medicine. The aim of this therapy is to reduce the connectivity between some components inside the brain which are responsible for causing stress. This computational model aspires to realistically demonstrate the activation of different portions of brain when the therapy is applied. The cognitive model starts with a situation of strong and continuous stress in an individual and after using fluoxetine the stress level begins to decrease over time. As a result, the patient will have a reduced stress level compared to not using drug.
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hal-02331346 , version 1 (24-10-2019)

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S. Sahand Mohammadi Ziabari. An Adaptive Temporal-Causal Network Model for Stress Extinction Using Fluoxetine. 15th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2019, Hersonissos, Greece. pp.107-119, ⟨10.1007/978-3-030-19823-7_8⟩. ⟨hal-02331346⟩
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