Estimating mental states of a depressed person with bayesian networks

Michel C.A. Klein, Gabriele Modena

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

Abstract

In this work in progress paper we present an approach based on Bayesian Networks to model the relationship between mental states and empirical observations in a depressed person. We encode relationships and domain expertise as a Hierarchical Bayesian Network. Mental states are represented as latent (hidden) variables and the measurements found in the data are encoded as a probability distribution generated by such latent variables; we provide examples of how the network can be used to estimate mental states.

Original languageEnglish
Title of host publicationContemporary Challenges and Solutions in Applied Artificial Intelligence
Pages163-168
Number of pages6
Volume489
DOIs
Publication statusPublished - 2013

Publication series

NameStudies in Computational Intelligence
Volume489
ISSN (Print)1860949X

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Bayesian networks
Probability distributions

Cite this

Klein, M. C. A., & Modena, G. (2013). Estimating mental states of a depressed person with bayesian networks. In Contemporary Challenges and Solutions in Applied Artificial Intelligence (Vol. 489, pp. 163-168). (Studies in Computational Intelligence; Vol. 489). https://doi.org/10.1007/978-3-319-00651-2_22
Klein, Michel C.A. ; Modena, Gabriele. / Estimating mental states of a depressed person with bayesian networks. Contemporary Challenges and Solutions in Applied Artificial Intelligence. Vol. 489 2013. pp. 163-168 (Studies in Computational Intelligence).
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Klein, MCA & Modena, G 2013, Estimating mental states of a depressed person with bayesian networks. in Contemporary Challenges and Solutions in Applied Artificial Intelligence. vol. 489, Studies in Computational Intelligence, vol. 489, pp. 163-168. https://doi.org/10.1007/978-3-319-00651-2_22

Estimating mental states of a depressed person with bayesian networks. / Klein, Michel C.A.; Modena, Gabriele.

Contemporary Challenges and Solutions in Applied Artificial Intelligence. Vol. 489 2013. p. 163-168 (Studies in Computational Intelligence; Vol. 489).

Research output: Chapter in Book / Report / Conference proceedingChapterAcademicpeer-review

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Klein MCA, Modena G. Estimating mental states of a depressed person with bayesian networks. In Contemporary Challenges and Solutions in Applied Artificial Intelligence. Vol. 489. 2013. p. 163-168. (Studies in Computational Intelligence). https://doi.org/10.1007/978-3-319-00651-2_22