381 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- University of TorontoCA46 papers
- SickKids FoundationCA15 papers
- University College LondonGB11 papers
- Public Health OntarioCA8 papers
- Institute for Clinical Evaluative SciencesCA7 papers
- Stanford UniversityUS5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Toronto Western HospitalCA4 papers
- University of California, BerkeleyUS4 papers
- Centro de Investigación y Docencia EconómicasMX3 papers
- Harvard UniversityUS3 papers
- Johns Hopkins UniversityUS3 papers
9 papers · 1 filter
Virtual Reality for Synergistic Surgical Training and Data Generation
Adnan Munawar, Zhaoshuo Li, Punit Kunjam +7
Surgical simulators not only allow planning and training of complex procedures, but also offer the ability to generate structured data for algorithm development, which may be appli…
Assembly of Model Postsynaptic Densities Involves Interactions Auxiliary to Stoichiometric Binding
Yi-Hsuan Lin, Haowei Wu, Bowen Jia +2
The assembly of functional biomolecular condensates often involves liquid-liquid phase separation (LLPS) of proteins with multiple modular domains, which can be folded or conformat…
A Tutorial on Time-Dependent Cohort State-Transition Models in R using a Cost-Effectiveness Analysis Example
Fernando Alarid-Escudero, Eline M. Krijkamp, Eva A. Enns +4
In an introductory tutorial, we illustrated building cohort state-transition models (cSTMs) in R, where the state transitions probabilities were constant over time. However, in pra…
Parametric G-computation for Compatible Indirect Treatment Comparisons with Limited Individual Patient Data
Antonio Remiro-Azócar, Anna Heath, Gianluca Baio
Population adjustment methods such as matching-adjusted indirect comparison (MAIC) are increasingly used to compare marginal treatment effects when there are cross-trial difference…
Towards Robust Classification Model by Counterfactual and Invariant Data Generation
Chun-Hao Chang, George Alexandru Adam, Anna Goldenberg
Despite the success of machine learning applications in science, industry, and society in general, many approaches are known to be non-robust, often relying on spurious correlation…
Unsupervised Representation Learning for Time Series with Temporal Neighborhood Coding
Sana Tonekaboni, Danny Eytan, Anna Goldenberg
Time series are often complex and rich in information but sparsely labeled and therefore challenging to model. In this paper, we propose a self-supervised framework for learning ge…
About Explicit Variance Minimization: Training Neural Networks for Medical Imaging With Limited Data Annotations
Dmitrii Shubin, Danny Eytan, Sebastian D. Goodfellow
Self-supervised learning methods for computer vision have demonstrated the effectiveness of pre-training feature representations, resulting in well-generalizing Deep Neural Network…
The AL-Gaussian Distribution as the Descriptive Model for the Internal Proactive Inhibition in the Standard Stop Signal Task
Mohsen Soltanifar, Michael Escobar, Annie Dupuis +2
Measurements of response inhibition components of reactive inhibition and proactive inhibition within the stop signal paradigm have been of special interest for researchers since t…
A Simple Explicit-Solvent Model of Polyampholyte Phase Behaviors and its Ramifications for Dielectric Effects in Biomolecular Condensates
Jonas Wessén, Tanmoy Pal, Suman Das +2
Biomolecular condensates such as membraneless organelles, underpinned by liquid-liquid phase separation (LLPS), are important for physiological function, with electrostatics -- amo…