Publications

Individual differences in interpersonal coordination
Julia Ayache
Guillaume Dumas
A. Sumich
D. Kuss
Darren Rhodes
Nadja Heym
2020-06-18
(publié)
doi.org
Special Issue on Novel Informatics Approaches to COVID-19 Research
Hua Xu
David Buckeridge
Fei Wang Guest Editors
2020-06-17
Journal of Biomedical Informatics (publié)
doi.org
User-Centered Design for Promoting Patient Engagement in Chronic Diseases Management: The Development of CONCERTO+
Marie-Pierre Gagnon
Mame Ndiaye
Alain Larouche
Guylaine Chabot
Christian Chabot
Ronald Buyl
Jean-Paul Fortin
Anik Giguère
Annie LeBlanc
France Légaré
Aude Motulsky
Claude Sicotte
Holly O Witteman
Eric Kavanagh
Frédéric Lépinay
Jacynthe Roberge
Hina Hakim
Myriam Brunet-Gauthier
Carole Délétroz
Samira Abbasgholizadeh-Rahimi … (voir 2 de plus)
Jack Tchuente
Maxime Sasseville
Multimorbidity increases care needs among people with chronic diseases. In order to support communication between patients, their informal c… (voir plus)aregivers and their healthcare teams, we developed CONCERTO+, a patient portal for chronic disease management in primary care. A user-centered design comprising 3 iterations with patients and informal caregivers was performed. Clinicians were also invited to provide feedback on the feasibility of the solution. Several improvements were brought to CONCERTO+, and it is now ready to be implemented in real-life setting.
2020-06-16
Medical Informatics Europe (publié)
doi.org
To Each Optimizer a Norm, To Each Norm its Generalization
Sharan Vaswani
Reza Babanezhad Harikandeh
Jose Gallego
Aaron Mishkin
Simon Lacoste-Julien
Nicolas Le Roux
We study the implicit regularization of optimization methods for linear models interpolating the training data in the under-parametrized and… (voir plus) over-parametrized regimes. Since it is difficult to determine whether an optimizer converges to solutions that minimize a known norm, we flip the problem and investigate what is the corresponding norm minimized by an interpolating solution. Using this reasoning, we prove that for over-parameterized linear regression, projections onto linear spans can be used to move between different interpolating solutions. For under-parameterized linear classification, we prove that for any linear classifier separating the data, there exists a family of quadratic norms ||.||_P such that the classifier's direction is the same as that of the maximum P-margin solution. For linear classification, we argue that analyzing convergence to the standard maximum l2-margin is arbitrary and show that minimizing the norm induced by the data results in better generalization. Furthermore, for over-parameterized linear classification, projections onto the data-span enable us to use techniques from the under-parameterized setting. On the empirical side, we propose techniques to bias optimizers towards better generalizing solutions, improving their test performance. We validate our theoretical results via synthetic experiments, and use the neural tangent kernel to handle non-linear models.
2020-06-11
ArXiv (prépublication)
arxiv.org
arxiv.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
A Large-Scale, Open-Domain, Mixed-Interface Dialogue-Based ITS for STEM
Iulian V. Serban
Varun Gupta
Ekaterina Kochmar
Dung D. Vu
Robert Belfer
Joelle Pineau
Aaron Courville
Laurent Charlin
Yoshua Bengio
2020-06-10
Artificial Intelligence in Education (publié)
doi.org
arxiv.org
Halting Time is Predictable for Large Models: A Universality Property and Average-Case Analysis
Courtney Paquette
Bart van Merriënboer
Fabian Pedregosa
2020-06-08
ArXiv (preprint)
doi.org
arxiv.org
Multi-agent Assortment Optimization in Sequential Matching Markets
Alfredo Torrico
Margarida Carvalho
Andrea Lodi
2020-06-08
ArXiv (prépublication)
arxiv.org
arxiv.org
Provable Guarantees for General Two-sided Sequential Matching Markets
Alfredo Torrico
Margarida Carvalho
Andrea Lodi
Two-sided markets have become increasingly more important during the last years, mostly because of their numerous applications in housing, l… (voir plus)abor and dating. Consumer-supplier matching platforms pose several technical challenges, specially due to the trade-off between recommending suitable suppliers to consumers and avoiding collisions among consumers' preferences. In this work, we study a general version of the two-sided sequential matching model introduced by Ashlagi et al. (2019). The setting is the following: we (the platform) offer a menu of suppliers to each consumer. Then, every consumer selects, simultaneously and independently, to match with a supplier or to remain unmatched. Suppliers observe the subset of consumers that selected them, and choose either to match a consumer or leave the system. Finally, a match takes place if both the consumer and the supplier sequentially select each other. Each agent's behavior is probabilistic and determined by a regular discrete choice model. Our objective is to choose an assortment family that maximizes the expected cardinality of the matching. Given the computational complexity of the problem, we show several provable guarantees for the general model, which in particular, significantly improve the approximation factors previously obtained.
2020-06-08
arXiv.org (prépublication)
dblp.uni-trier.de
Dark control: The default mode network as a reinforcement learning agent
Elvis Dohmatob
Guillaume Dumas
Danilo Bzdok
2020-06-05
Human Brain Mapping (publié)
doi.org
Prioritization of patients access to outpatient augmentative and alternative communication services in Quebec: a decision tool
Samira Abbasgholizadeh-Rahimi
Julien Dery
Marie‐eve Lamontagne
Ali Jamshidi
Emilie Lacroix
Angel B. Ruiz
Daoud Ait-Kadi
F. Routhier
Abstract Purpose A large number of people living with a chronic disability wait a long time to access publicly funded rehabilitation service… (voir plus)s such as Augmentative and Alternative Communication (AAC) services, and there is no standardized tool to prioritize these patients. We aimed to develop a prioritization tool to improve the organization and access to the care for this population. Methods In this sequential mixed methods study, we began with a qualitative phase in which we conducted semi-structured interviews with 14 stakeholders including patients, their caregivers, and AAC service providers in Quebec City, Canada to gather their ideas about prioritization criteria. Then, during a half-day consensus group meeting with stakeholders, using a consensus-seeking technique (i.e. Technique for Research of Information by Animation of a Group of Experts), we reached consensus on the most important prioritization criteria. These criteria informed the quantitative phase in which used an electronic questionnaire to collect stakeholders’ views regarding the relative weights for each of the selected criteria. We analyzed these data using a hybrid quantitative method called group based fuzzy analytical hierarchy process, to obtain the importance weights of the selected eight criteria. Results Analyses of the interviews revealed 48 criteria. Collectively, the stakeholders reached consensus on eight criteria, and through the electronic questionnaire they defined the selected criteria’s importance weights. The selected eight prioritization criteria and their importance weights are: person’s safety (weight: 0.274), risks development potential (weight: 0.144), psychological well-being (weight: 0.140), physical well-being (weight: 0.124), life prognosis (weight: 0.106), possible impact on social environment (weight: 0.085), interpersonal relationships (weight: 0.073), and responsibilities and social role (weight: 0.054). Conclusion In this study, we co-developed a prioritization decision tool with the key stakeholders for prioritization of patients who are referred to AAC services in rehabilitation settings. IMPLICATIONS FOR REHABILIATION Studies in Canada have shown that people in Canada with a need for rehabilitation services are not receiving publicly available services in a timely manner. There is no standardized tool for the prioritization of AAC patients. In this mixed methods study, we co-developed a prioritization tool with key stakeholders for prioritization of patients who are referred to AAC services in a rehabilitation center in Quebec, Canada.
2020-06-05
Disability and Rehabilitation: Assistive Technology (published)
doi.org
Prioritization of patients access to outpatient augmentative and alternative communication services in Quebec: a decision tool
Samira Abbasgholizadeh-Rahimi
Julien Dery
Marie-Eve Lamontagne
Afshin Jamshidi
Emilie Lacroix
Angel Ruiz
Daoud Ait-Kadi
François Routhier
2020-06-05
Disability and Rehabilitation: Assistive Technology (publié)
doi.org