Grant: CIHR Fellowship
Direct Payment
$150,000.00
Using machine learning to curb the opioid epidemic in Canada and the United States
FY 2020-21
Summary
Canada and the United States are facing an unprecedented public health crisis of opioid-related morbidity and mortality. The opioid epidemic is a complex problem, and one of the major drivers of this epidemic is the untreated opioid use disorder (OUD). There is limited scientific evidence regarding the individual, interpersonal, communal, and societal level factors contributing to the risk of developing OUD. Therefore, this postdoctoral research program aims to: (1) review the scientific literature on predictors of OUD for people who use opioids; and (2) build comprehensive and reliable predictive models for OUD using machine learning methods, which can overcome the critical challenges often faced by traditional statistical models when handling high-dimensional data. This postdoctoral research program will make important contributions to understanding mechanisms underlying development of OUD, informing design of impactful prevention and treatment strategies to curb the opioid overdose crisis, and ultimately improving clinical care and public health policy priority setting.
Department
Program
CIHR Fellowship
Recipient
Location
Massachusetts, United States of America
Type
Grant
Source
CIHR Funding Decisions Database
As published
Id
440546
Name
Dong Huiru
Region
Massachusetts
Country
United States of America
Orgtype
Research Institution
Instname2
Neurosciences, Mental Health and Addiction
Theme2
Social / Cultural / Environmental / Population Health
Prcname2
Health Research Training A - Post-PhD (HTA)
Projecttitle
Using machine learning to curb the opioid epidemic in Canada and the United States
Programtype2
Fellowship Programs
Orgnameinp2
Direct Payment
Cihramount2
$150,000
Cihrequipment2
$0
Programname2
CIHR Fellowship
Keyworddelim
Covid-19 Pandemic; Drug Overdose; Machine Learning; Meta-Analysis; Opioid Epidemic; Opioid Use Disorder; Predictive Model; Social Determinants Of Health; Substance Use; Systematic Review
Abstract
Canada and the United States are facing an unprecedented public health crisis of opioid-related morbidity and mortality. The opioid epidemic is a complex problem, and one of the major drivers of this epidemic is the untreated opioid use disorder (OUD). There is limited scientific evidence regarding the individual, interpersonal, communal, and societal level factors contributing to the risk of developing OUD. Therefore, this postdoctoral research program aims to: (1) review the scientific literature on predictors of OUD for people who use opioids; and (2) build comprehensive and reliable predictive models for OUD using machine learning methods, which can overcome the critical challenges often faced by traditional statistical models when handling high-dimensional data. This postdoctoral research program will make important contributions to understanding mechanisms underlying development of OUD, informing design of impactful prevention and treatment strategies to curb the opioid overdose crisis, and ultimately improving clinical care and public health policy priority setting.
Competitiondate
202012
Approvedterm2
3 yrs 0 mth
Pinamesdelim
Dong, Huiru
Approvedterm
3 ans 0 mois
Cihrcontribution2
~ $150,000~ $0~