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Raissa Souza
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Explainable classification of Parkinson’s disease using deep learning trained on a large multi-center database of T1-weighted MRI datasets
M Camacho, M Wilms, P Mouches, H Almgren, R Souza, R Camicioli, ...
NeuroImage: Clinical 38, 103405, 2023
312023
Assessment of lipid and metabolite changes in obese calf muscle using multi-echo echo-planar correlated spectroscopic imaging
R Nagarajan, CL Carpenter, CC Lee, N Michael, MK Sarma, R Souza, ...
Scientific reports 7 (1), 17338, 2017
162017
Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data
R Souza, M Wilms, M Camacho, GB Pike, R Camicioli, O Monchi, ...
Journal of the American Medical Informatics Association 30 (12), 1925-1933, 2023
122023
An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction
R Souza, P Mouches, M Wilms, A Tuladhar, S Langner, ND Forkert
Journal of the American Medical Informatics Association 30 (1), 112-119, 2023
92023
Pilot assessment of brain metabolism in perinatally HIV-infected youths using accelerated 5D echo planar J-resolved spectroscopic imaging
Z Iqbal, NE Wilson, MA Keller, DE Michalik, JA Church, K Nielsen-Saines, ...
PloS one 11 (9), e0162810, 2016
92016
Identifying biases in a multicenter MRI database for Parkinson's disease classification: Is the disease classifier a secret site classifier?
R Souza, A Winder, EAM Stanley, V Vigneshwaran, M Camacho, ...
IEEE Journal of Biomedical and Health Informatics, 2024
82024
A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm
R Souza, EAM Stanley, M Camacho, R Camicioli, O Monchi, Z Ismail, ...
Frontiers in Artificial Intelligence 7, 1301997, 2024
62024
Towards objective and systematic evaluation of bias in artificial intelligence for medical imaging
EAM Stanley, R Souza, AJ Winder, V Gulve, K Amador, M Wilms, ...
Journal of the American Medical Informatics Association 31 (11), 2613-2621, 2024
52024
A comparative analysis of the impact of data distribution on distributed learning with a traveling model for brain age prediction
R Souza, A Aulakh, P Mouches, A Tuladhar, M Wilms, S Langner, ...
Medical Imaging 2022: Imaging Informatics for Healthcare, Research, and …, 2022
52022
Federated Learning Using Variable Local Training for Brain Tumor Segmentation
A Tuladhar, L Tyagi, R Souza, ND Forkert
International MICCAI Brainlesion Workshop, 392-404, 2021
42021
Multi-institutional travelling model for tumor segmentation in MRI datasets
R Souza, A Tuladhar, P Mouches, M Wilms, L Tyagi, ND Forkert
International MICCAI Brainlesion Workshop, 420-432, 2021
42021
Towards objective and systematic evaluation of bias in medical imaging AI
EAM Stanley, R Souza, A Winder, V Gulve, K Amador, M Wilms, ...
arXiv preprint arXiv:2311.02115, 2023
32023
On the Relationship Between Open Science in Artificial Intelligence for Medical Imaging and Global Health Equity
R Souza, EAM Stanley, ND Forkert
Workshop on Clinical Image-Based Procedures, 289-300, 2023
32023
Improved multi-site Parkinson’s disease classification using neuroimaging data with counterfactual inference
V Vigneshwaran, M Wilms, MIC Camacho, R Souza, N Forkert
Medical Imaging with Deep Learning, 1304-1317, 2024
22024
An analysis of intensity harmonization techniques for Parkinson’s multi-site MRI datasets
R Souza, EAM Stanley, M Camacho, M Wilms, ND Forkert
Medical Imaging 2023: Computer-Aided Diagnosis 12465, 570-576, 2023
12023
Where, why, and how is bias learned in medical image analysis models? A study of bias encoding within convolutional networks using synthetic data
EAM Stanley, R Souza, M Wilms, ND Forkert
EBioMedicine 111, 2025
2025
Foundation model-driven distributed learning for enhanced retinal age prediction
C Nielsen, R Souza, M Wilms, ND Forkert
Journal of the American Medical Informatics Association 31 (11), 2550-2559, 2024
2024
Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis
EAM Stanley, R Souza, AJ Winder, M Wilms, GB Pike, G Dagasso, ...
MICCAI Workshop on Fairness of AI in Medical Imaging, 163-175, 2024
2024
Do Sites Benefit Equally from Distributed Learning in Medical Image Analysis?
R Souza, EAM Stanley, R Camicioli, O Monchi, Z Ismail, M Wilms, ...
MICCAI Workshop on Fairness of AI in Medical Imaging, 119-128, 2024
2024
HarmonyTM: multi-center data harmonization applied to distributed learning for Parkinson’s disease classification
R Souza, EAM Stanley, V Gulve, J Moore, C Kang, R Camicioli, O Monchi, ...
Journal of Medical Imaging 11 (5), 054502-054502, 2024
2024
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