A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences

Jon Hael Brenas, Eun Kyong Shin, Arash Shaban-Nejad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Adverse Childhood Experiences (ACEs) are negative events or states that affect children, with lasting impacts throughout their adulthood. ACES are considered one of the major risk factors for several adverse health outcomes and are associated with low quality of life and many detrimental social and economic consequences. In order to enact better surveillance of ACEs and their associated conditions, it is instrumental to provide tools to detect, monitor and respond effectively. In this paper, we present a recommender system tasked with simplifying data collection, access, and reasoning related to ACEs. The recommender system uses both semantic and statistical methods to enable content and context-based filtering.

Original languageEnglish (US)
Title of host publicationHealth Informatics Vision
Subtitle of host publicationFrom Data via Information to Knowledge
EditorsJohn Mantas, Arie Hasman, Parisis Gallos, Aikaterini Kolokathi, Mowafa S. Househ, Joseph Liaskos
PublisherIOS Press
Pages332-335
Number of pages4
ISBN (Electronic)9781614999867
DOIs
StatePublished - Jan 1 2019

Publication series

NameStudies in Health Technology and Informatics
Volume262
ISSN (Print)0926-9630
ISSN (Electronic)1879-8365

Fingerprint

Recommender systems
Semantics
Economics
Quality of Life
Health
Statistical methods
N-(2-acetamido)-2-aminoethanesulfonic acid

All Science Journal Classification (ASJC) codes

  • Biomedical Engineering
  • Health Informatics
  • Health Information Management

Cite this

Brenas, J. H., Shin, E. K., & Shaban-Nejad, A. (2019). A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences. In J. Mantas, A. Hasman, P. Gallos, A. Kolokathi, M. S. Househ, & J. Liaskos (Eds.), Health Informatics Vision: From Data via Information to Knowledge (pp. 332-335). (Studies in Health Technology and Informatics; Vol. 262). IOS Press. https://doi.org/10.3233/SHTI190086

A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences. / Brenas, Jon Hael; Shin, Eun Kyong; Shaban-Nejad, Arash.

Health Informatics Vision: From Data via Information to Knowledge. ed. / John Mantas; Arie Hasman; Parisis Gallos; Aikaterini Kolokathi; Mowafa S. Househ; Joseph Liaskos. IOS Press, 2019. p. 332-335 (Studies in Health Technology and Informatics; Vol. 262).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Brenas, JH, Shin, EK & Shaban-Nejad, A 2019, A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences. in J Mantas, A Hasman, P Gallos, A Kolokathi, MS Househ & J Liaskos (eds), Health Informatics Vision: From Data via Information to Knowledge. Studies in Health Technology and Informatics, vol. 262, IOS Press, pp. 332-335. https://doi.org/10.3233/SHTI190086
Brenas JH, Shin EK, Shaban-Nejad A. A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences. In Mantas J, Hasman A, Gallos P, Kolokathi A, Househ MS, Liaskos J, editors, Health Informatics Vision: From Data via Information to Knowledge. IOS Press. 2019. p. 332-335. (Studies in Health Technology and Informatics). https://doi.org/10.3233/SHTI190086
Brenas, Jon Hael ; Shin, Eun Kyong ; Shaban-Nejad, Arash. / A Hybrid Recommender System to Guide Assessment and Surveillance of Adverse Childhood Experiences. Health Informatics Vision: From Data via Information to Knowledge. editor / John Mantas ; Arie Hasman ; Parisis Gallos ; Aikaterini Kolokathi ; Mowafa S. Househ ; Joseph Liaskos. IOS Press, 2019. pp. 332-335 (Studies in Health Technology and Informatics).
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