Computational analysis of the adaptive causal relationships between cannabis, anxiety and sleep

Merijn van Leeuwen, Kirsten Wolthuis, Jan Treur*

*Corresponding author for this work

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review

Abstract

In this paper an adaptive computational temporal-causal network model is presented to analyse the dynamic and adaptive relationships between cannabis usage, anxiety and sleep. The model has been used to simulate different well-known scenarios varying from intermittent usage to longer periods of usage interrupted by attempts to quit and to constant usage based on full addiction. It is described how the model has been verified and validated by empirical information from the literature.

Original languageEnglish
Title of host publicationComputational Science – ICCS 2020
Subtitle of host publication20th International Conference, Amsterdam, The Netherlands, June 3–5, 2020, Proceedings, Part I
EditorsValeria V. Krzhizhanovskaya, Gábor Závodszky, Michael H. Lees, Peter M.A. Sloot, Peter M.A. Sloot, Peter M.A. Sloot, Jack J. Dongarra, Sérgio Brissos, João Teixeira
PublisherSpringer
Pages357-370
Number of pages14
Volume1
ISBN (Electronic)9783030503710
ISBN (Print)9783030503703
DOIs
Publication statusPublished - 2020
Event20th International Conference on Computational Science, ICCS 2020 - Amsterdam, Netherlands
Duration: 3 Jun 20205 Jun 2020

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume12137 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th International Conference on Computational Science, ICCS 2020
CountryNetherlands
CityAmsterdam
Period3/06/205/06/20

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