167 citations · 272 across the 13 of their papers we have counts for
13 papers
Shape-Based Inductive Bias for Glioma Grading from Tumor Contours
Puneet Velidi, Michelle F. Miranda, Farouk Nathoo +2
Glioma grading from tumor contours is often treated as a pixel problem even when the signal of interest is shape. We align closed contours with a functional shape-alignment framewo…
A Wavelet-Based Framework for Mapping Long Memory in Resting-State fMRI: Age-Related Changes in the Hippocampus from the ADHD-200 Dataset
Yasaman Shahhosseini, Cédric Beaulac, Farouk S. Nathoo +1
Functional magnetic resonance imaging (fMRI) time series are known to exhibit long-range temporal dependencies that challenge traditional modeling approaches. In this study, we pro…
Functional Autoencoder for Smoothing and Representation Learning
Sidi Wu, Cédric Beaulac, Jiguo Cao
A common pipeline in functional data analysis is to first convert the discretely observed data to smooth functions, and then represent the functions by a finite-dimensional vector…
Neural Networks for Scalar Input and Functional Output
Sidi Wu, Cédric Beaulac, Jiguo Cao
The regression of a functional response on a set of scalar predictors can be a challenging task, especially if there is a large number of predictors, or the relationship between th…
Neuroimaging Feature Extraction using a Neural Network Classifier for Imaging Genetics
Cédric Beaulac, Sidi Wu, Erin Gibson +5
A major issue in the association of genes to neuroimaging phenotypes is the high dimension of both genetic data and neuroimaging data. In this article, we tackle the latter problem…
Predicting Time-to-conversion for Dementia of Alzheimer's Type using Multi-modal Deep Survival Analysis
Ghazal Mirabnahrazam, Da Ma, Cédric Beaulac +8
Dementia of Alzheimer's Type (DAT) is a complex disorder influenced by numerous factors, but it is unclear how each factor contributes to disease progression. An in-depth examinati…
A moment-matching metric for latent variable generative models
Cédric Beaulac
It can be difficult to assess the quality of a fitted model when facing unsupervised learning problems. Latent variable models, such as variation autoencoders and Gaussian mixture…
Introducing a new high-resolution handwritten digits data set with writer characteristics
Cédric Beaulac, Jeffrey S. Rosenthal
The contributions in this article are two-fold. First, we introduce a new hand-written digit data set that we collected. It contains high-resolution images of hand-written The cont…
An evaluation of machine learning techniques to predict the outcome of children treated for Hodgkin-Lymphoma on the AHOD0031 trial: A report from the Children's Oncology Group
Cédric Beaulac, Jeffrey S. Rosenthal, Qinglin Pei +3
In this manuscript we analyze a data set containing information on children with Hodgkin Lymphoma (HL) enrolled on a clinical trial. Treatments received and survival status were co…
A Deep Latent-Variable Model Application to Select Treatment Intensity in Survival Analysis
Cédric Beaulac, Jeffrey S. Rosenthal, David Hodgson
In the following short article we adapt a new and popular machine learning model for inference on medical data sets. Our method is based on the Variational AutoEncoder (VAE) framew…
BEST : A decision tree algorithm that handles missing values
Cédric Beaulac, Jeffrey S. Rosenthal
The main contribution of this paper is the development of a new decision tree algorithm. The proposed approach allows users to guide the algorithm through the data partitioning pro…
Narrow Artificial Intelligence with Machine Learning for Real-Time Estimation of a Mobile Agents Location Using Hidden Markov Models
Cédric Beaulac, Fabrice Larribe
We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that…
Predicting University Students' Academic Success and Major using Random Forests
Cédric Beaulac, Jeffrey S. Rosenthal
In this article, a large data set containing every course taken by every undergraduate student in a major university in Canada over 10 years is analysed. Modern machine learning al…