Raissa Souza

Publication Activity (10 Years)

Years Active: 2021-2024
Publications (10 Years): 10

Top Topics

Systematic Evaluation

Probabilistic Classifiers

Distributed Learning

Brain Tumor Segmentation

Top Venues

BrainLes@MICCAI (2)

J. Am. Medical Informatics Assoc.

IEEE J. Biomed. Health Informatics

Publications

Raissa Souza, Emma A. M. Stanley, Milton Camacho, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert
A multi-center distributed learning approach for Parkinson's disease classification using the traveling model paradigm. Frontiers Artif. Intell. 7 (2024)
Raissa Souza, Anthony J. Winder, Emma A. M. Stanley, Vibujithan Vigneshwaran, Milton Camacho, Richard Camicioli, Oury Monchi, Matthias Wilms, Nils D. Forkert
Identifying Biases in a Multicenter MRI Database for Parkinson's Disease Classification: Is the Disease Classifier a Secret Site Classifier? IEEE J. Biomed. Health Informatics 28 (4) (2024)
Vibujithan Vigneshwaran, Matthias Wilms, Milton Ivan Camacho, Raissa Souza, Nils D. Forkert
Improved multi-site Parkinson's disease classification using neuroimaging data with counterfactual inference. MIDL (2023)
Raissa Souza, Matthias Wilms, Milton Camacho, G. Bruce Pike, Richard Camicioli, Oury Monchi, Nils D. Forkert
Image-encoded biological and non-biological variables may be used as shortcuts in deep learning models trained on multisite neuroimaging data. J. Am. Medical Informatics Assoc. 30 (12) (2023)
Raissa Souza, Emma A. M. Stanley, Milton Camacho, Matthias Wilms, Nils D. Forkert
An analysis of intensity harmonization techniques for Parkinson's multi-site MRI datasets. Medical Imaging: Computer-Aided Diagnosis (2023)
Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Vedant Gulve, Kimberly Amador, Matthias Wilms, Nils D. Forkert
Towards objective and systematic evaluation of bias in medical imaging AI. CoRR (2023)
Raissa Souza, Emma A. M. Stanley, Nils D. Forkert
On the Relationship Between Open Science in Artificial Intelligence for Medical Imaging and Global Health Equity. CLIP/FAIMI/EPIMI@MICCAI (2023)
Raissa Souza, Pauline Mouches, Matthias Wilms, Anup Tuladhar, Sönke Langner, Nils D. Forkert
An analysis of the effects of limited training data in distributed learning scenarios for brain age prediction. J. Am. Medical Informatics Assoc. 30 (1) (2022)
Anup Tuladhar, Lakshay Tyagi, Raissa Souza, Nils D. Forkert
Federated Learning Using Variable Local Training for Brain Tumor Segmentation. BrainLes@MICCAI (2) (2021)
Raissa Souza, Anup Tuladhar, Pauline Mouches, Matthias Wilms, Lakshay Tyagi, Nils D. Forkert
Multi-institutional Travelling Model for Tumor Segmentation in MRI Datasets. BrainLes@MICCAI (2) (2021)