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ORCIDEmma A. M. Stanley
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2020 – today
- 2024
[j3]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)- [j2]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 artificial intelligence for medical imaging. J. Am. Medical Informatics Assoc. 31(11): 2613-2621 (2024) - [j1]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): 2047-2054 (2024) - [c8]Matthias Wilms, Ahmad O. Ahsan, Erik Y. Ohara, Gabrielle Dagasso, Elizabeth Macavoy, Emma A. M. Stanley, Vibujithan Vigneshwaran, Nils D. Forkert:
A Lightweight 3D Conditional Diffusion Model for Self-explainable Brain Age Prediction in Adults and Children. MLCN@MICCAI 2024: 57-67 - [c7]Raissa Souza, Emma A. M. Stanley, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert:
Do Sites Benefit Equally from Distributed Learning in Medical Image Analysis? FAIMI/EPIMI@MICCAI 2024: 119-128 - [c6]Emma A. M. Stanley, Raissa Souza, Anthony J. Winder, Matthias Wilms, G. Bruce Pike, Gabrielle Dagasso, Christopher Nielsen, Sarah J. MacEachern, Nils D. Forkert:
Assessing the Impact of Sociotechnical Harms in AI-Based Medical Image Analysis. FAIMI/EPIMI@MICCAI 2024: 163-175 - 2023
- [c5]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: 289-300 - [c4]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. Computer-Aided Diagnosis 2023 - [c3]Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert:
A Flexible Framework for Simulating and Evaluating Biases in Deep Learning-Based Medical Image Analysis. MICCAI (2) 2023: 489-499 - [i1]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 abs/2311.02115 (2023) - 2022
- [c2]Emma A. M. Stanley, Deepthi Rajashekar, Pauline Mouches, Matthias Wilms, Kira Plettl, Nils D. Forkert:
A fully convolutional neural network for explainable classification of attention deficit hyperactivity disorder. Computer-Aided Diagnosis 2022 - [c1]Emma A. M. Stanley, Matthias Wilms, Nils D. Forkert:
Disproportionate Subgroup Impacts and Other Challenges of Fairness in Artificial Intelligence for Medical Image Analysis. EPIMI/ML-CDS@MICCAI 2022: 14-25
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