Social networks and automated mental health screening

Song, Insu, and Vong, John (2014) Social networks and automated mental health screening. In: Lech, Margaret, Song, Insu, Yellowlees, Peter, and Diederich, Joachim, (eds.) Mental Health Informatics. Studies in Computational Intelligence, 491 . Springer, Berlin, Germany, pp. 107-123.

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Abstract

A health social network is an online information service which facilitates information sharing between closely related members of a community. The main means of finding patients with similar health conditions has been based on labor-intensive methods, such as searching the Internet. Also, because of the privacy and security issues of health information systems, it is often difficult to find patients who can support each other in the community. Over the years, many automated recommender systems have been developed for social networking. We propose a social networking framework for patient care, where health service providers facilitate social links between parents using similarities of mental health conditions. A machine learning approach was developed to automatically generate keywords for mental health descriptions that can be used to screen for mental health conditions and to then group individuals with similar mental health conditions. Keywords are generated from sources such as conversations on online forums. These keywords are then used to identify similarities between mental health descriptions, in order to recommend a community of related patients.

Item ID: 30709
Item Type: Book Chapter (Research - B1)
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ISBN: 978-3-642-38549-0
ISSN: 1860-9503
Date Deposited: 01 Apr 2014 00:22
FoR Codes: 08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080109 Pattern Recognition and Data Mining @ 50%
08 INFORMATION AND COMPUTING SCIENCES > 0801 Artificial Intelligence and Image Processing > 080107 Natural Language Processing @ 50%
SEO Codes: 92 HEALTH > 9202 Health and Support Services > 920203 Diagnostic Methods @ 50%
92 HEALTH > 9202 Health and Support Services > 920209 Mental Health Services @ 50%
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