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dc.contributor.authorDelahunty, Fionn
dc.contributor.authorJohansson, Robert
dc.contributor.authorMihael, Arcan
dc.date.accessioned2019-06-28T13:34:04Z
dc.date.available2019-06-28T13:34:04Z
dc.date.issued2019
dc.identifier.citationDelahunty, Fionn , Johansson, Robert , & Arcan, Mihael (2019). Passive diagnosis incorporating the PHQ-4 for depression and anxiety. Paper presented at the Social Media Mining for Health Applications Workshop, DOI: 10.13025/ee3h-yz88en_IE
dc.identifier.urihttp://hdl.handle.net/10379/15256
dc.description.abstractDepression and anxiety are the two most prevalent mental health disorders worldwide, impacting the lives of millions of people each year. In this work, we develop and evaluate a multilabel, multidimensional deep neural network designed to predict PHQ-4 scores based on individuals written text. Our system outperforms random baseline metrics and provides a novel approach to how we can predict psychometric scores from written text. Additionally, we explore how this architecture can be applied to analyse social media data.en_IE
dc.description.sponsorshipThis publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) under Grant Number SFI/12/RC/2289 (Insight).en_IE
dc.formatapplication/pdfen_IE
dc.language.isoenen_IE
dc.publisherNUI Galwayen_IE
dc.relation.ispartofSocial Media Mining for Health Applications Workshopen
dc.subjectPassive diagnosisen_IE
dc.subjectPHQ-4en_IE
dc.subjectDepressionen_IE
dc.subjectAnxietyen_IE
dc.titlePassive diagnosis incorporating the PHQ-4 for depression and anxietyen_IE
dc.typeWorkshop paperen_IE
dc.date.updated2019-06-28T11:45:34Z
dc.identifier.doi10.13025/ee3h-yz88
dc.local.publishedsourcehttps://doi.org/10.13025/ee3h-yz88
dc.description.peer-reviewedpeer-reviewed
dc.contributor.funderScience Foundation Irelanden_IE
dc.internal.rssid16672644
dc.local.contactMihael Arcan. Email: mihael.arcan@insight-centre.org
dc.local.copyrightcheckedYes
dc.local.versionACCEPTED
dcterms.projectinfo:eu-repo/grantAgreement/SFI/SFI Research Centres/12/RC/2289/IE/INSIGHT - Irelands Big Data and Analytics Research Centre/en_IE
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