Publications

Adaptation, Translation, and Validation of a Patient-Reported Experience Measure for Children and Young People for the Canadian Context.
Zanib Nafees
Julia Ferreira
Elena Guadagno
Jo Wray
Agneta Anderzén-Carlsson
Dan Poenaru
2024-02-01
Journal of Pediatric Surgery (published)
doi.org
Adaptation, Translation, and Validation of a Patient-Reported Experience Measure for Children and Young People for the Canadian Context
Zanib Nafees
Julia Ferreira
Elena Guadagno
Jo Wray
Agneta Anderzén-Carlsson
Dan Poenaru
2024-02-01
Journal of Pediatric Surgery (published)
doi.org
Adaptation, Translation, and Validation of a Patient-Reported Experience Measure for Children and Young People for the Canadian Context.
Zanib Nafees
Julia Ferreira
Elena Guadagno
Jo Wray
Agneta Anderzén-Carlsson
Dan Poenaru
2024-02-01
Journal of Pediatric Surgery (published)
doi.org
Amplifying Pathological Detection in EEG Signaling Pathways through Cross-Dataset Transfer Learning
Mohammad Javad Darvishi Bayazi
Mohammad S. Ghaemi
Timothee LESORT
Md Rifat Arefin
Jocelyn Faubert
Irina Rish
2024-02-01
Computers in Biology and Medicine (published)
doi.org
arxiv.org
Author Correction: BCG immunization induces CX3CR1hi effector memory T cells to provide cross-protection via IFN-γ-mediated trained immunity.
Kim A. Tran
Erwan Pernet
Mina Sadeghi
Jeffrey Downey
Julia Chronopoulos
Elizabeth Lapshina
Oscar Tsai
Eva Kaufmann
Jun Ding
Maziar Divangahi
2024-02-01
Nature Immunology (published)
doi.org
Automatic segmentation of the spinal cord nerve rootlets
Jan Valosek
Theo Mathieu
Raphaëlle Schlienger
Olivia S. Kowalczyk
Julien Cohen-Adad
Abstract Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the … (see more)spinal cord. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access 3T MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from three datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 ± 0.16 (mean ± standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation ≤ 1.41%), as well as low inter-session variability (coefficient of variation ≤ 1.30%), indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.
2024-02-01
ArXiv (preprint)
doi.org
arxiv.org
Automatic segmentation of the spinal cord nerve rootlets
Jan Valosek
Theo Mathieu
Raphaëlle Schlienger
Olivia S. Kowalczyk
Julien Cohen-Adad
Abstract Precise identification of spinal nerve rootlets is relevant to delineate spinal levels for the study of functional activity in the … (see more)spinal cord. The goal of this study was to develop an automatic method for the semantic segmentation of spinal nerve rootlets from T2-weighted magnetic resonance imaging (MRI) scans. Images from two open-access 3T MRI datasets were used to train a 3D multi-class convolutional neural network using an active learning approach to segment C2-C8 dorsal nerve rootlets. Each output class corresponds to a spinal level. The method was tested on 3T T2-weighted images from three datasets unseen during training to assess inter-site, inter-session, and inter-resolution variability. The test Dice score was 0.67 ± 0.16 (mean ± standard deviation across testing images and rootlets levels), suggesting a good performance. The method also demonstrated low inter-vendor and inter-site variability (coefficient of variation ≤ 1.41%), as well as low inter-session variability (coefficient of variation ≤ 1.30%), indicating stable predictions across different MRI vendors, sites, and sessions. The proposed methodology is open-source and readily available in the Spinal Cord Toolbox (SCT) v6.2 and higher.
2024-02-01
ArXiv (preprint)
doi.org
arxiv.org
Co-developing The Canadian MPS Registry: A longitudinal rare disease patient registry
John J. Mitchell
Michal Inbar-Feigenberg
Kim Angel
Pranesh Chakraborty
Monica Lamoureux
John Adams
Beth K. Potter
Sylvia Stockler-Ipsirolgu
Alison H. Howie
Alex Pace
Nancy J. Butcher
Cheryl Greenberg
Robin Hayeems
Anne-Marie Laberge
Jeff Round
Martin Offringa
Maryam Oskoui
Chelsea Ruth
Andreas Schulze
Kathy N. Speechley … (see 4 more)
Kednapa Thavorn
Yannis Trakadis
Kumanan Wilson
Thierry Lacaze
2024-02-01
Molecular Genetics and Metabolism (published)
doi.org
Co-developing The Canadian MPS Registry: A longitudinal rare disease patient registry
John J. Mitchell
Michal Inbar-Feigenberg
Kim Angel
Pranesh Chakraborty
Monica Lamoureux
John Adams
Beth K. Potter
Sylvia Stockler-Ipsirolgu
Alison H. Howie
Alex Pace
Nancy J. Butcher
Cheryl Greenberg
Robin Hayeems
Anne-Marie Laberge
Jeff Round
Martin Offringa
Maryam Oskoui
Chelsea Ruth
Andreas Schulze
Kathy N. Speechley … (see 4 more)
Kednapa Thavorn
Yannis Trakadis
Kumanan Wilson
Thierry Lacaze
2024-02-01
Molecular Genetics and Metabolism (published)
doi.org
Data science opportunities of large language models for neuroscience and biomedicine
Danilo Bzdok
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Siva Reddy
2024-02-01
Neuron (published)
doi.org
Data science opportunities of large language models for neuroscience and biomedicine
Danilo Bzdok
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Siva Reddy
2024-02-01
Neuron (published)
doi.org
Data science opportunities of large language models for neuroscience and biomedicine
Danilo Bzdok
Andrew Thieme
Oleksiy Levkovskyy
Paul Wren
Thomas Ray
Siva Reddy
2024-02-01
Neuron (published)
doi.org