Portrait de David Buckeridge

David Buckeridge

Membre académique associé
Professeur titulaire, McGill University, Département d'épidémiologie, biostatistique et santé au travail
Sujets de recherche
Apprentissage automatique médical
Google Scholar
LinkedIn

Biographie

David Buckeridge est professeur titulaire à l'École de santé des populations et de santé mondiale de l'Université McGill, responsable de la santé numérique au Centre universitaire de santé McGill et directeur scientifique exécutif pour l'Agence de la santé publique du Canada. Titulaire d'une chaire de recherche du Canada (niveau 1) en informatique de la santé et en science des données, il a établi les projections concernant la demande dans le système de santé du Québec, dirigé la gestion des données et l'analyse pour le groupe de travail sur l'immunité canadienne et aidé l'Organisation mondiale de la santé à surveiller l'immunité mondiale contre le SRAS-CoV-2. Il est titulaire d'un doctorat en médecine (Université Queen's), d'une maîtrise en épidémiologie (Université de Toronto) et d'un doctorat en informatique biomédicale (Université Stanford), et est membre du Collège royal des médecins du Canada.

Étudiants actuels

Eva Gao
Doctorat - McGill
yachen li Li
Maîtrise recherche - McGill
Aidan Licoppe
Maîtrise recherche - McGill
Github
Yannan Shen
Maîtrise recherche - McGill

Publications

Correction to: Why public health matters today and tomorrow: the role of applied public health research
Lindsay McLaren
Paula Braitstein
David Buckeridge
Damien Contandriopoulos
Maria I. Creatore
Guy Faulkner
David Hammond
Steven J. Hoffman
Yan Kestens
Scott Leatherdale
Jonathan McGavock
Wendy V. Norman
Candace Nykiforuk
Valéry Ridde
Janet Smylie
The article “Why public health matters today and tomorrow: the role of applied public health research,” written by Lindsay McLaren et al… (voir plus)., was originally published Online First without Open Access.
2020-09-02
Canadian Journal of Public Health = Revue Canadienne de Santé Publique (publié)
doi.org
SeroTracker: a global SARS-CoV-2 seroprevalence dashboard
Rahul K. Arora
Abel Joseph
Jordan Van Wyk
Simona Rocco
Austin Atmaja
Ewan May
Tingting Yan
Niklas Bobrovitz
Jonathan Chevrier
Matthew P. Cheng
Tyler Williamson
David Buckeridge
2020-08-04
Lancet. Infectious Diseases (Print) (publié)
doi.org
Precision, Equity, and Public Health and Epidemiology Informatics – A Scoping Review
David Buckeridge
2020-08-01
Yearbook of Medical Informatics (publié)
doi.org
Special Issue on Novel Informatics Approaches to COVID-19 Research
Huanan Xu
David Buckeridge
Fei Wang Guest Editors
2020-06-17
Journal of Biomedical Informatics (publié)
doi.org
Glossary for public health surveillance in the age of data science
Arnaud Chiolero
David Buckeridge
Public health surveillance is the ongoing systematic collection, analysis and interpretation of data, closely integrated with the timely dis… (voir plus)semination of the resulting information to those responsible for preventing and controlling disease and injury. With the rapid development of data science, encompassing big data and artificial intelligence, and with the exponential growth of accessible and highly heterogeneous health-related data, from healthcare providers to user-generated online content, the field of surveillance and health monitoring is changing rapidly. It is, therefore, the right time for a short glossary of key terms in public health surveillance, with an emphasis on new data-science developments in the field.
2020-06-10
Journal of Epidemiology and Community Health (publié)
doi.org
Precision public health: Dream or reality?
Maureen Dobbins
David Buckeridge
2020-06-04
Canada communicable disease report = Releve des maladies transmissibles au Canada (publié)
doi.org
Failure to follow medication changes made at hospital discharge is associated with adverse events in 30 days
Daniala L Weir
Aude Motulsky
Michal Abrahamowicz
Todd C. Lee
Steven Morgan
David Buckeridge
Robyn Tamblyn
2020-05-20
Health Services Research (publié)
doi.org
Clustering for Continuous-Time Hidden Markov Models.
Yu Luo
David A. Stephens
David Buckeridge
We develop clustering procedures for longitudinal trajectories based on a continuous-time hidden Markov model (CTHMM) and a generalized line… (voir plus)ar observation model. Specifically in this paper, we carry out infinite mixture model-based clustering for CTHMM and achieve inference using Markov chain Monte Carlo (MCMC). Specifically, for Bayesian nonparametric inference using a Dirichlet process mixture model, we utilize restricted Gibbs sampling split-merge proposals to expedite the MCMC algorithm. We employ the proposed algorithm to the simulated data as well as a large real data example, and the results demonstrate the desired performance of the new sampler.
Bayesian latent multi‐state modeling for nonequidistant longitudinal electronic health records
Yu Luo
David A. Stephens
Aman Verma
David Buckeridge
2020-03-31
Biometrics (publié)
doi.org
Both New and Chronic Potentially Inappropriate Medications Continued at Hospital Discharge Are Associated With Increased Risk of Adverse Events
Daniala L Weir
Todd C. Lee
Emily G. McDonald
Aude Motulsky
Michal Abrahamowicz
Steven Morgan
David Buckeridge
Robyn Tamblyn
2020-03-31
Journal of The American Geriatrics Society (publié)
doi.org
Multinational Investigation of Fracture Risk with Antidepressant Use by Class, Drug, and Indication
Robyn Tamblyn
David W. Bates
David Buckeridge
William G. Dixon
Nadyne Girard
Jennifer S. Haas
Bettina Habib
Usman Iqbal
Jack Li
Therese Sheppard
Antidepressants increase the risk of falls and fracture in older adults. However, risk estimates vary considerably even in comparable popula… (voir plus)tions, limiting the usefulness of current evidence for clinical decision making. Our aim was to apply a common protocol to cohorts of older antidepressant users in multiple jurisdictions to estimate fracture risk associated with different antidepressant classes, drugs, doses, and potential treatment indications.
2020-03-17
Journal of the American Geriatrics Society (publié)
doi.org
Seven pillars of precision digital health and medicine
Arash Shaban-Nejad
Martin Michalowski
Niels Peek
John S. Brownstein
David Buckeridge
2020-03-01
Artificial Intelligence in Medicine (publié)
doi.org