328 citations · 406 across the 12 of their papers we have counts for
12 papers
CableInspect-AD: An Expert-Annotated Anomaly Detection Dataset
Akshatha Arodi, Margaux Luck, Jean-Luc Bedwani +5
Machine learning models are increasingly being deployed in real-world contexts. However, systematic studies on their transferability to specific and critical applications are under…
Self-supervised multimodal neuroimaging yields predictive representations for a spectrum of Alzheimer's phenotypes
Alex Fedorov, Eloy Geenjaar, Lei Wu +7
Recent neuroimaging studies that focus on predicting brain disorders via modern machine learning approaches commonly include a single modality and rely on supervised over-parameter…
Self-Supervised Multimodal Domino: in Search of Biomarkers for Alzheimer's Disease
Alex Fedorov, Tristan Sylvain, Eloy Geenjaar +7
Sensory input from multiple sources is crucial for robust and coherent human perception. Different sources contribute complementary explanatory factors. Similarly, research studies…
On self-supervised multi-modal representation learning: An application to Alzheimer's disease
Alex Fedorov, Lei Wu, Tristan Sylvain +5
Introspection of deep supervised predictive models trained on functional and structural brain imaging may uncover novel markers of Alzheimer's disease (AD). However, supervised tra…
Cross-Modal Information Maximization for Medical Imaging: CMIM
Tristan Sylvain, Francis Dutil, Tess Berthier +4
In hospitals, data are siloed to specific information systems that make the same information available under different modalities such as the different medical imaging exams the pa…
Navigation Agents for the Visually Impaired: A Sidewalk Simulator and Experiments
Martin Weiss, Simon Chamorro, Roger Girgis +7
Millions of blind and visually-impaired (BVI) people navigate urban environments every day, using smartphones for high-level path-planning and white canes or guide dogs for local i…