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

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

Maîtrise recherche - McGill
Maîtrise recherche - McGill
Doctorat - McGill
Maîtrise recherche - McGill
Maîtrise recherche - McGill
Maîtrise recherche - McGill

Publications

Parametric models for combined failure time data from an incident cohort study and a prevalent cohort study with follow-up
James H. McVittie
David B. Wolfson
David A. Stephens
Vittorio Addona
COVI-AgentSim: an Agent-based Model for Evaluating Methods of Digital Contact Tracing
Prateek Gupta
Martin Weiss
Nasim Rahaman
Hannah Alsdurf
abhinav sharma
Nanor Minoyan
Soren Harnois-Leblanc
Victor Schmidt
Pierre-Luc St-Charles
Tristan Deleu
andrew williams
Akshay Patel
Meng Qu
Olexa Bilaniuk
gaetan caron
pierre luc carrier
satya ortiz gagne
Marc-Andre Rousseau
Joumana Ghosn
Yang Zhang
Bernhard Schölkopf
Joanna Merckx
NutriQuébec: a unique web-based prospective cohort study to monitor the population’s eating and other lifestyle behaviours in the province of Québec
Annie Lapointe
Catherine Laramée
Ariane Belanger-Gravel
Sophie Desroches
Didier Garriguet
Lise Gauvin
Simone Lemieux
Céline Plante
Benoit Lamarche
Correction to: Why public health matters today and tomorrow: the role of applied public health research
Lindsay McLaren
Paula Braitstein
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.
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
Precision, Equity, and Public Health and Epidemiology Informatics – A Scoping Review
Special Issue on Novel Informatics Approaches to COVID-19 Research
Hua Xu
Fei Wang Guest Editors
Glossary for public health surveillance in the age of data science
Arnaud Chiolero
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.
Precision public health: Dream or reality?
Maureen Dobbins
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
Robyn Tamblyn
Clustering for Continuous-Time Hidden Markov Models.
Yu Luo
David A. Stephens
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