Grad-CAM helps interpret the deep learning models trained to classify multiple sclerosis types using clinical brain magnetic resonance imaging Y Zhang, D Hong, D McClement, O Oladosu, G Pridham, G Slaney Journal of Neuroscience Methods 353, 109098, 2021 | 84 | 2021 |
Characterizing structural changes with evolving remyelination following experimental demyelination using high angular resolution diffusion MRI and texture analysis T Luo, O Oladosu, KS Rawji, P Zhai, G Pridham, S Hossain, Y Zhang Journal of Magnetic Resonance Imaging 49 (6), 1750-1759, 2019 | 23 | 2019 |
Strategies for handling missing data that improve Frailty Index estimation and predictive power: lessons from the NHANES dataset G Pridham, K Rockwood, A Rutenberg GeroScience 44 (2), 897-923, 2022 | 11 | 2022 |
Texture analysis in brain T2 and diffusion MRI differentiates histology-verified grey and white matter pathology types in multiple sclerosis Z Hosseinpour, L Jonkman, O Oladosu, G Pridham, GB Pike, M Inglese, ... Journal of Neuroscience Methods 379, 109671, 2022 | 7 | 2022 |
Acoustic radiation force impulse and conventional ultrasound in the prediction of cirrhosis complicating fatty liver: does body mass index independently alter the results? A Medellin, G Pridham, SJ Urbanski, S Jayakumar, SR Wilson Ultrasound in Medicine & Biology 45 (12), 3160-3171, 2019 | 7 | 2019 |
A discrete polar Stockwell transform for enhanced characterization of tissue structure using MRI G Pridham, MD Steenwijk, JJG Geurts, Y Zhang Magnetic resonance in medicine 80 (6), 2731-2743, 2018 | 6 | 2018 |
Efficient representations of binarized health deficit data: the frailty index and beyond G Pridham, K Rockwood, A Rutenberg Geroscience 45 (3), 1687-1711, 2023 | 5 | 2023 |
Evaluation of discrete orthogonal versus polar Stockwell Transform for local multi-resolution texture analysis using brain MRI of multiple sclerosis patients G Pridham, O Oladosu, Y Zhang Magnetic Resonance Imaging 72, 150-158, 2020 | 4 | 2020 |
A metric learning method for estimating myelin content based on T2-weighted MRI from a de-and re-myelination model of multiple sclerosis G Pridham, S Hossain, KS Rawji, Y Zhang Plos one 16 (4), e0249460, 2021 | 1 | 2021 |
Quantitative phase and texture angularity analysis of brain white matter lesions in multiple sclerosis S Baxandall, S Sharma, P Zhai, G Pridham, Y Zhang Medical Imaging 2018: Image Processing 10574, 350-356, 2018 | 1 | 2018 |
Photodisintegration of the Deuteron at 18 MeV using Linearly Polarized Photons G Pridham University of Saskatchewan, 2014 | 1 | 2014 |
Dynamical network stability analysis of multiple biological ages provides a framework for understanding the aging process G Pridham, AD Rutenberg The Journals of Gerontology, Series A: Biological Sciences and Medical …, 2024 | | 2024 |
Network dynamical stability analysis reveals key “mallostatic” natural variables that erode homeostasis and drive age-related decline of health G Pridham, AD Rutenberg Scientific Reports 13 (1), 22140, 2023 | | 2023 |
Network dynamical stability analysis of homeostasis reveals "mallostasis": biological equilibria drifting towards worsening health with age G Pridham, A Rutenberg arXiv:2306.12448, 2023 | | 2023 |
Modelling disease impact: lifespan reduction is greatest for young adults in an exogenous damage model of disease R Tobin, G Pridham, D Rutenberg, Andrew arXiv:2305.06808, 2023 | | 2023 |
The Frailty Index, Missing Data, and Imputation G Pridham, A Rutenberg Innovation in Aging 4 (Suppl 1), 923, 2020 | | 2020 |
Characterizing MS lesion pathology using directional metrics of auto-correlation in MRI Y Zhang, G Pridham MULTIPLE SCLEROSIS JOURNAL 24, 432-433, 2018 | | 2018 |
D (γ, n) H: Photodisintegration of the Deuteron at 18 MeV using Linearly Polarized Photons G Pridham | | 2014 |
Photodisintegration of the Deuteron at 20 MeV using Circularly Polarized Photons G Pridham | | 2014 |
Measurement of neutron recoil polarization in low energy photodisintegration of deuterium BE Norum, S Tkachenko, RA Lindgren, PN Seo, R Duve, H Arenhövel, ... | | 2013 |