4 papers
AdapDISCOM: An Adaptive Sparse Regression Method for High-Dimensional Multimodal Data With Block-Wise Missingness and Measurement Errors
Maimouna Baldé, Abdoul O. Diakité, Claudia Moreau +6
Multimodal high-dimensional data are increasingly prevalent in biomedical research, yet they are often compromised by block-wise missingness and measurement errors, posing signific…
Numerical Uncertainty in Linear Registration: An Experimental Study
Niusha Mirhakimi, Yohan Chatelain, Tristan Glatard +1
While linear registration is a critical step in MRI preprocessing pipelines, its numerical uncertainty is understudied. Using Monte-Carlo Arithmetic (MCA) simulations, we assessed…
Predicting Parkinson's disease trajectory using clinical and functional MRI features: a reproduction and replication study
Elodie Germani, Nikhil Baghwat, Mathieu Dugré +7
Parkinson's disease (PD) is a common neurodegenerative disorder with a poorly understood physiopathology and no established biomarkers for the diagnosis of early stages and for pre…
fastHDMI: Fast Mutual Information Estimation for High-Dimensional Data
Kai Yang, Masoud Asgharian, Nikhil Bhagwat +2
In this paper, we introduce fastHDMI, a Python package designed for efficient variable screening in high-dimensional datasets, particularly neuroimaging data. This work pioneers th…