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Author
Md Fitrat Hossain
;
Thomas Kissane
;
Priyanka Annapureddy
;
Wylie Frydrychowicz
;
Sheikh Iqbal Ahamed
;
Naveen Bansal
;
Praveen Madiraju
;
Niharika Jain
;
Mark Flower
;
Katinka Hooyer
;
Lisa Rein
;
Zeno Franco
Title
Implementing Algorithmic Crisis Alerts in mHealth Systems for Veterans with PTSD
Type
Conference Article
Year
2020
Publication
ISCRAM 2020 Conference Proceedings – 17th International Conference on Information Systems for Crisis Response and Management
Abbreviated Journal
Iscram 2020
Volume
Issue
Pages
122-133
Keywords
Crisis
;
Machine Learning Algorithms
;
mHealth
;
PTSD
Abstract
This paper seeks to establish a machine learning driven method by which a military veteran with Post-Traumatic Stress Disorder (PTSD) is classified as being in a crisis situation or not, based upon a given set of criteria. Optimizing alerting decision rules is critical to ensure that veterans at highest risk for mental health crisis rapidly receive additional attention. Subject matter experts in our team (a psychologist, a medical anthropologist, and an expert veteran), defined acute crisis, early warning signs and long-term crisis from this dataset. First, we used a decision tree to find an early time point when the peer mentors (who are also veterans) need to observe the behavior of veterans to make a decision about conducting an intervention. Three different machine learning algorithms were used to predict long term crisis using acute crisis and early warning signs within the determined time point.
Address
Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Marquette University; Mental Health America; Medical College of Wisconsin; Medical College of Wisconsin; Medical College of Wisconsin
Corporate Author
Thesis
Publisher
Virginia Tech
Place of Publication
Blacksburg, VA (USA)
Editor
Amanda Hughes; Fiona McNeill; Christopher W. Zobel
Language
English
Summary Language
English
Original Title
Series Editor
Series Title
Abbreviated Series Title
Series Volume
Series Issue
Edition
ISSN
978-1-949373-27-12
ISBN
2411-3398
Medium
Track
AI Systems for Crisis and Risks
Expedition
Conference
17th International Conference on Information Systems for Crisis Response and Management
Notes
mdfitrat.hossain@marquette.edu
Approved
no
Call Number
Serial
2213
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