55 citations · 63 across the 5 of their papers we have counts for
5 papers · 1 filter
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…
Learning to rank for censored survival data
Margaux Luck, Tristan Sylvain, Joseph Paul Cohen +3
Survival analysis is a type of semi-supervised ranking task where the target output (the survival time) is often right-censored. Utilizing this information is a challenge because i…
Rule-Mining based classification: a benchmark study
Margaux Luck, Nicolas Pallet, Cecilia Damon
This study proposed an exhaustive stable/reproducible rule-mining algorithm combined to a classifier to generate both accurate and interpretable models. Our method first extracts r…
Deep Learning for Patient-Specific Kidney Graft Survival Analysis
Margaux Luck, Tristan Sylvain, Héloïse Cardinal +2
An accurate model of patient-specific kidney graft survival distributions can help to improve shared-decision making in the treatment and care of patients. In this paper, we propos…