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Kimberly Amador
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2020 – today
- 2026
[i2]Asbjørn Munk, Stefano Cerri, Vardan Nersesjan, Christian Hedeager Krag, Jakob Ambsdorf, Pablo Rocamora-García, Julia Machnio, Peirong Liu, Suhyun Ahn, Nasrin Akbari, Yasmina Al Khalil, Kimberly Amador, Sina Amirrajab, Tal Arbel, Meritxell Bach Cuadra, Ujjwal Baid, Bhakti Baheti, Jaume Banus, Kamil Barbierik, Christoph Brune, Yansong Bu, Baptiste Callard, Yuhan Chen, Cornelius Crijnen, Corentin Dancette, Peter Drotár, Prasad Dutande, Nils D. Forkert, Saurabh Garg, Jakub Gazda, Matej Gazda, Benoît Gérin, Partha Ghosh, Weikang Gong, Pedro M. Gordaliza, Sam Hashemi, Tobias Heimann, Fucang Jia, Jiexin Jiang, Emily Kaczmarek, Chris Kang, Seung Kwan Kang, Mohammad Khazaei, Julien Khlaut, Petros Koutsouvelis, Jae Sung Lee, Yuchong Li, Mengye Lyu, Mingchen Ma, Anant Madabhushi, Klaus H. Maier-Hein, Pierre Manceron, Andrés Martínez Mora, Moona Mazher, Felix Meister, Nataliia Molchanova, Steven A. Niederer, Leonard Nürnberg, Jinah Park, Abdul Qayyum, Jonas Richiardi, Antoine Saporta, Branislav Setlák, Ning Shen, Justin Szeto, Constantin Ulrich, Puru Vaish, Vibujithan Vigneshwaran, Leroy Volmer, Zihao Wang, Siqi Wei, Anthony J. Winder, Jelmer M. Wolterink, Maxence Wynen, Chang Yang, Si Young Yie, Mostafa Mehdipour-Ghazi, Akshay Pai, Espen Jimenez-Solem, Sebastian Nørgaard Llambias, Mikael Boesen, Michael Eriksen Benros, Juan Eugenio Iglesias, Mads Nielsen:
Towards Brain MRI Foundation Models for the Clinic: Findings from the FOMO25 Challenge. CoRR abs/2604.11679 (2026)- 2025
[j6]Kimberly Amador
, Noah Pinel
, Anthony J. Winder
, Jens Fiehler, Matthias Wilms
, Nils D. Forkert
:
A cross-attention-based deep learning approach for predicting functional stroke outcomes using 4D CTP imaging and clinical metadata. Medical Image Anal. 99: 103381 (2025)
[j5]Raissa Souza
, Emma A. M. Stanley
, Anthony J. Winder, Chris Kang
, Kimberly Amador
, Erik Y. Ohara, Gabrielle Dagasso, Richard Camicioli, Oury Monchi, Zahinoor Ismail, Matthias Wilms, Nils D. Forkert:
Self-supervised identification and elimination of harmful datasets in distributed machine learning for medical image analysis. npj Digit. Medicine 8(1) (2025)- 2024
[j4]Alejandro Gutierrez
, Kimberly Amador, Anthony J. Winder
, Matthias Wilms, Jens Fiehler, Nils D. Forkert:
Annotation-free prediction of treatment-specific tissue outcome from 4D CT perfusion imaging in acute ischemic stroke. Comput. Medical Imaging Graph. 114: 102376 (2024)
[j3]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)
[j2]Kimberly Amador
, Alejandro Gutierrez, Anthony J. Winder
, Jens Fiehler, Matthias Wilms
, Nils D. Forkert
:
Providing clinical context to the spatio-temporal analysis of 4D CT perfusion to predict acute ischemic stroke lesion outcomes. J. Biomed. Informatics 149: 104567 (2024)
[c4]Kimberly Amador, Anthony J. Winder, Noah Pinel, Jens Fiehler, Matthias Wilms, Nils D. Forkert:
Unveiling the Temporal Patterns of a 4D CTP Stroke Lesion Outcome Prediction Model Through Attention Analysis. ISBI 2024: 1-5
[c3]Kimberly Amador, Anthony J. Winder, Nils D. Forkert:
Spatio-Temporal Deep Learning for Final Infarct Prediction Using Acute Stroke CT Perfusion Data. SWITCH/ISLES@MICCAI 2024: 83-88- 2023
[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
[j1]Kimberly Amador
, Matthias Wilms
, Anthony J. Winder
, Jens Fiehler
, Nils D. Forkert
:
Predicting treatment-specific lesion outcomes in acute ischemic stroke from 4D CT perfusion imaging using spatio-temporal convolutional neural networks. Medical Image Anal. 82: 102610 (2022)
[c2]Kimberly Amador, Anthony J. Winder
, Jens Fiehler, Matthias Wilms, Nils D. Forkert:
Hybrid Spatio-Temporal Transformer Network for Predicting Ischemic Stroke Lesion Outcomes from 4D CT Perfusion Imaging. MICCAI (3) 2022: 644-654- 2021
[c1]Kimberly Amador
, Matthias Wilms, Anthony J. Winder, Jens Fiehler, Nils D. Forkert:
Stroke Lesion Outcome Prediction Based on 4D CT Perfusion Data Using Temporal Convolutional Networks. MIDL 2021: 22-33
Coauthor Index
aka: Nils D. Forkert

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last updated on 2026-05-10 00:50 CEST by the dblp team
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