Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model

Sajjad Fouladvand; Emily R. Hankosky; Darren W. Henderson; Heather Bush; Jin Chen; Linda P. Dwoskin; Patricia R. Freeman; Kathleen Kantak; Jeffery Talbert; Shiqiang Tao; Guo Qiang Zhang

doi:10.1109/ICHI-W.2018.00014

Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model

Sajjad Fouladvand, Emily R. Hankosky, Darren W. Henderson, Heather Bush, Jin Chen, Linda P. Dwoskin, Patricia R. Freeman, Kathleen Kantak, Jeffery Talbert, Shiqiang Tao, Guo Qiang Zhang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

About 20% of individuals with attention deficit hyperactivity disorder (ADHD) are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to ADHD medication is an important factor in the development of substance use disorder (SUD) phenotypes in adulthood, the long-Term impact of ADHD medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent ADHD patients in the Truven database indicates that temporal medication features are the important factors on the health consequences related to SUD and ADHD medication initiation during adolescence.

Original language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
Pages	49-50
Number of pages	2
ISBN (Electronic)	9781538667774
DOIs	https://doi.org/10.1109/ICHI-W.2018.00014
State	Published - Jul 16 2018
Event	6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 - New York, United States Duration: Jun 4 2018 → Jun 7 2018

Publication series

Name	Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018

Conference

Conference	6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018
Country/Territory	United States
City	New York
Period	6/4/18 → 6/7/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

Keywords

Attention Deficit-Hyperactivity Disorder
Big Data
Long-Short Term Memory Model
Substance Use Disorder

ASJC Scopus subject areas

Information Systems and Management
Health Informatics

Access to Document

10.1109/ICHI-W.2018.00014

Cite this

Fouladvand, S., Hankosky, E. R., Henderson, D. W., Bush, H., Chen, J., Dwoskin, L. P., Freeman, P. R., Kantak, K., Talbert, J., Tao, S., & Zhang, G. Q. (2018). Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 (pp. 49-50). Article 8411680 (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018). https://doi.org/10.1109/ICHI-W.2018.00014

Fouladvand, Sajjad ; Hankosky, Emily R. ; Henderson, Darren W. et al. / Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model. Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. 2018. pp. 49-50 (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018).

@inproceedings{2816a43a2cac40999fc79899a291d427,

title = "Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model",

abstract = "About 20\% of individuals with attention deficit hyperactivity disorder (ADHD) are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to ADHD medication is an important factor in the development of substance use disorder (SUD) phenotypes in adulthood, the long-Term impact of ADHD medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent ADHD patients in the Truven database indicates that temporal medication features are the important factors on the health consequences related to SUD and ADHD medication initiation during adolescence.",

keywords = "Attention Deficit-Hyperactivity Disorder, Big Data, Long-Short Term Memory Model, Substance Use Disorder",

author = "Sajjad Fouladvand and Hankosky, \{Emily R.\} and Henderson, \{Darren W.\} and Heather Bush and Jin Chen and Dwoskin, \{Linda P.\} and Freeman, \{Patricia R.\} and Kathleen Kantak and Jeffery Talbert and Shiqiang Tao and Zhang, \{Guo Qiang\}",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018 ; Conference date: 04-06-2018 Through 07-06-2018",

year = "2018",

month = jul,

day = "16",

doi = "10.1109/ICHI-W.2018.00014",

language = "English",

series = "Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018",

pages = "49--50",

booktitle = "Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018",

}

Fouladvand, S, Hankosky, ER, Henderson, DW, Bush, H, Chen, J, Dwoskin, LP , Freeman, PR, Kantak, K, Talbert, J, Tao, S & Zhang, GQ 2018, Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model. in Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018., 8411680, Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018, pp. 49-50, 6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018, New York, United States, 6/4/18. https://doi.org/10.1109/ICHI-W.2018.00014

Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model. / Fouladvand, Sajjad; Hankosky, Emily R.; Henderson, Darren W. et al.
Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. 2018. p. 49-50 8411680 (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model

AU - Fouladvand, Sajjad

AU - Hankosky, Emily R.

AU - Henderson, Darren W.

AU - Bush, Heather

AU - Chen, Jin

AU - Dwoskin, Linda P.

AU - Freeman, Patricia R.

AU - Kantak, Kathleen

AU - Talbert, Jeffery

AU - Tao, Shiqiang

AU - Zhang, Guo Qiang

PY - 2018/7/16

Y1 - 2018/7/16

N2 - About 20% of individuals with attention deficit hyperactivity disorder (ADHD) are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to ADHD medication is an important factor in the development of substance use disorder (SUD) phenotypes in adulthood, the long-Term impact of ADHD medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent ADHD patients in the Truven database indicates that temporal medication features are the important factors on the health consequences related to SUD and ADHD medication initiation during adolescence.

AB - About 20% of individuals with attention deficit hyperactivity disorder (ADHD) are first diagnosed during adolescence. While preclinical experiments suggest that adolescent-onset exposure to ADHD medication is an important factor in the development of substance use disorder (SUD) phenotypes in adulthood, the long-Term impact of ADHD medication initiated during adolescence has been largely unexplored in humans. Our analysis of 11,624 adolescent ADHD patients in the Truven database indicates that temporal medication features are the important factors on the health consequences related to SUD and ADHD medication initiation during adolescence.

KW - Attention Deficit-Hyperactivity Disorder

KW - Big Data

KW - Long-Short Term Memory Model

KW - Substance Use Disorder

UR - http://www.scopus.com/inward/record.url?scp=85051050511&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85051050511&partnerID=8YFLogxK

U2 - 10.1109/ICHI-W.2018.00014

DO - 10.1109/ICHI-W.2018.00014

M3 - Conference contribution

AN - SCOPUS:85051050511

T3 - Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018

SP - 49

EP - 50

BT - Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018

T2 - 6th IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018

Y2 - 4 June 2018 through 7 June 2018

ER -

Fouladvand S, Hankosky ER, Henderson DW, Bush H, Chen J, Dwoskin LP et al. Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model. In Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018. 2018. p. 49-50. 8411680. (Proceedings - 2018 IEEE International Conference on Healthcare Informatics Workshops, ICHI-W 2018). doi: 10.1109/ICHI-W.2018.00014

Predicting Substance Use Disorder in ADHD Patients using Long-Short Term Memory Model

Abstract

Publication series

Conference

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this