Félicitations aux titulaires d’une subvention pour l’analyse de données à partir de bases et de cohortes existantes
Le concours Subvention de fonctionnement : Analyse de données à partir de bases de données et de cohortes existantes de 2023, dirigé par l’IDSEA, en partenariat avec l’Institut des maladies infectieuses et immunitaires (IMII) et la Direction générale de la santé des Premières Nations et des Inuits (DGSPNI) de Services aux Autochtones Canada (SAC), et soutenu par l’Institut du cancer (IC), l’Institut de la santé circulatoire et respiratoire (ISCR), l’Institut de la santé des femmes et des hommes (ISFH), l’Institut des services et des politiques de la santé (ISPS) et l’Institut de l’appareil locomoteur et de l’arthrite (IALA) des IRSC, a permis de financer pas moins de 20 équipes de recherche qui feront usage de données tirées de cohortes, de bases de données, de plateformes de données et de catalogues de cohortes existants au Canada dans l’optique de contribuer au développement ou à la santé des enfants et des adolescents ainsi que de guider l’amélioration des résultats des patients, des populations et des systèmes. Félicitations à toutes les équipes financées.
- Marie C Arrieta Mendez, University of Calgary – Systems-level repertoire of human milk components as drivers of microbial and immune development in preterm infants
- Hilary Brown, University of Toronto – Immune-related disorders in adolescence and future risk of endometriosis: A population-based cohort study
- Ginny Brunton, University of Ontario Institute of Technology – Prevalence and outcomes of water birth versus 'land' birth in Ontario mothers and neonates at low risk of complications: a secondary analysis of routinely collected BORN data.
- Vincy Chan, University Health Network (Toronto) – A longitudinal, population-based birth cohort study to understand long-term health service use after sustaining a traumatic brain injury during childhood and adolescence
- Katherine T Cost, McMaster University – Temporal Trends in the Distribution of Child and Youth Mental Ill-Health from 1983 to 2023: Evidence from 4 General Population Based Samples in Ontario
- Claire de Oliveira, Centre de toxicomanie et de santé mentale – Understanding the impact of maternal depression on offspring later life socioeconomic outcomes
- Derek K Chu, McMaster University – Investigating the effect of prepartum, intrapartum, and postpartum factors and the Risk of Food Allergy in Children: Evidence from the CHILD Cohort Study
- Marie-Claude Geoffroy, CIUSSS de l'Ouest-de-l'Ile-de-Montréal-Hôpital Douglas – Mental Health of Sexual Diverse Youth
- Steven Hawken, Institut de recherche de l'Hôpital d'Ottawa – Deep Learning Models for Prediction of Pre-eclampsia from Prenatal Ultrasound Placental Imaging
- Ashraf Kharrat, Sinai Health System (Toronto) – Incidence and outcomes of neonatal septic shock in Canada: a nationwide population-based observational study
- Robert A Kleinman, Centre de toxicomanie et de santé mentale – Comparative effectiveness of medications for opioid use disorder among youth
- Azadeh Kushki, Holland Bloorview Kids Rehabilitation Hospital (Toronto) – Predicting medication usage for autistic children using machine learning
- Catherine A Lebel, University of Calgary – Uncovering the neurobiological underpinnings of learning to read and reading disorders
- Giulia Muraca, McMaster University – Mental illness among individuals with severe maternal morbidity
- Tamara L Taillieu, University of Manitoba – A Population-Based Examination of the Public Health Impacts of the Legalization of Recreational Use of Cannabis on Children and Youth from Manitoba
- Evelyne Touchette, Université du Québec à Trois-Rivières – Sleep is not just a matter of night: Understanding the etiology of naps in 2.5- to 6-year-olds
- Mark Wade, University of Toronto – Intergenerational transmission of early adversity from mothers to their children: Testing mechanisms in a large Canadian birth cohort
- Samantha L Wilson, McMaster University – Developing sex-specific predictive models for preeclampsia
- Lyndia (Chun) Wu, University of British Columbia – Using clinical polysomnography data and machine learning to determine minimum sensing requirements for pediatric sleep studies
- Aleksandra M Zuk, Queen's University (Kingston, Ontario) – Neonatal and Obstetric Health Outcomes among Women Diagnosed with Vasa Previa in Canada (NOHOW-VP)
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