First insights on a passive major depressive disorder prediction system with incorporated conversational chatbot

Fionn Delahunty, Ian D. Wood, Mihael Arcan

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

11 Citations (Scopus)
18 Downloads (Pure)

Abstract

Almost 50% of cases of major depressive disorder go undiagnosed. In this paper, we propose a passive diagnostic system that combines the areas of clinical psychology, machine learning and conversational dialogue systems. We have trained a dialogue system, powered by sequence-to-sequence neural networks that can have a real-time conversation with individuals. In tandem, we have developed specific machine learning classifiers that monitor the conversation and predict the presence or absence of certain crucial depression symptoms. This would facilitate real-time instant crisis support for those suffering from depression. Our evaluation metrics have suggested this could be a positive future direction of research in both developing more human like chatbots and identifying depression in written text. We hope this work may additionally have practical implications in the area of crisis support services for mental health organisations.
Original languageEnglish
Title of host publicationProceedings for the 26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science
EditorsRob Brennan, Joeran Beel, Ruth Byrne, Jeremy Debattista, Ademar Crotti Junior
Place of PublicationAachen, Germany
PublisherCEUR Workshop Proceedings
Pages1-12
Number of pages12
Publication statusPublished - 2018
Externally publishedYes
Event26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science - Dublin, Ireland
Duration: 6 Dec 20188 Dec 2018

Publication series

NameCEUR Workshop Proceedings
Volume2259
ISSN (Electronic)1613-0073

Conference

Conference26th AIAI Irish Conference on Artificial Intelligence and Cognitive Science
Country/TerritoryIreland
CityDublin
Period6/12/188/12/18

Bibliographical note

Version archived for private and non-commercial use with the permission of the author/s and according to publisher conditions. For further rights please contact the publisher.

Keywords

  • Depression
  • Social Media
  • Conversational Chatbot

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