Thomas J. Fuchs
Cited by
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Understanding neural networks through deep visualization
J Yosinski, J Clune, A Nguyen, T Fuchs, H Lipson
arXiv preprint arXiv:1506.06579, 2015
Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
G Campanella, MG Hanna, L Geneslaw, A Miraflor, ...
Nature medicine 25 (8), 1301-1309, 2019
DeepPET: A deep encoder–decoder network for directly solving the PET image reconstruction inverse problem
I Häggström, CR Schmidtlein, G Campanella, TJ Fuchs
Medical image analysis 54, 253-262, 2019
Computational pathology: challenges and promises for tissue analysis
TJ Fuchs, JM Buhmann
Computerized Medical Imaging and Graphics 35 (7-8), 515-530, 2011
TAK1 suppresses a NEMO-dependent but NF-κB-independent pathway to liver cancer
K Bettermann, M Vucur, J Haybaeck, C Koppe, J Janssen, F Heymann, ...
Cancer cell 17 (5), 481-496, 2010
Hybrid deep learning on single wide-field optical coherence tomography scans accurately classifies glaucoma suspects
H Muhammad, TJ Fuchs, N De Cuir, CG De Moraes, DM Blumberg, ...
Journal of glaucoma 26 (12), 1086-1094, 2017
Cancer genetics-guided discovery of serum biomarker signatures for diagnosis and prognosis of prostate cancer
I Cima, R Schiess, P Wild, M Kaelin, P Schüffler, V Lange, P Picotti, ...
Proceedings of the National Academy of Sciences 108 (8), 3342-3347, 2011
Whole slide imaging equivalency and efficiency study: experience at a large academic center
MG Hanna, VE Reuter, MR Hameed, LK Tan, S Chiang, C Sigel, ...
Modern Pathology 32 (7), 916-928, 2019
Quickly boosting decision trees–pruning underachieving features early
R Appel, T Fuchs, P Dollár, P Perona
International conference on machine learning, 594-602, 2013
Robot-centric activity prediction from first-person videos: What will they do to me?
MS Ryoo, TJ Fuchs, L Xia, JK Aggarwal, L Matthies
Proceedings of the tenth annual ACM/IEEE international conference on human …, 2015
Novel artificial intelligence system increases the detection of prostate cancer in whole slide images of core needle biopsies
P Raciti, J Sue, R Ceballos, R Godrich, JD Kunz, S Kapur, V Reuter, ...
Modern Pathology 33 (10), 2058-2066, 2020
Neuron geometry extraction by perceptual grouping in ssTEM images
V Kaynig, T Fuchs, JM Buhmann
2010 IEEE computer society conference on computer vision and pattern …, 2010
Prognostic relevance of Wnt-inhibitory factor-1 (WIF1) and Dickkopf-3 (DKK3) promoter methylation in human breast cancer
J Veeck, PJ Wild, T Fuchs, PJ Schüffler, A Hartmann, R Knüchel, E Dahl
BMC cancer 9, 1-13, 2009
H&E-stained whole slide image deep learning predicts SPOP mutation state in prostate cancer
AJ Schaumberg, MA Rubin, TJ Fuchs
BioRxiv, 064279, 2016
Machine learning approaches to analyze histological images of tissues from radical prostatectomies
A Gertych, N Ing, Z Ma, TJ Fuchs, S Salman, S Mohanty, S Bhele, ...
Computerized Medical Imaging and Graphics 46, 197-208, 2015
Risk-aware planetary rover operation: Autonomous terrain classification and path planning
M Ono, TJ Fuchs, A Steffy, M Maimone, J Yen
2015 IEEE aerospace conference, 1-10, 2015
A generalized computer vision approach to mapping crop fields in heterogeneous agricultural landscapes
SR Debats, D Luo, LD Estes, TJ Fuchs, KK Caylor
Remote Sensing of Environment 179, 210-221, 2016
The Bayesian group-lasso for analyzing contingency tables
S Raman, TJ Fuchs, PJ Wild, E Dahl, V Roth
Proceedings of the 26th Annual International Conference on Machine Learning …, 2009
Deep multi-magnification networks for multi-class breast cancer image segmentation
DJ Ho, DVK Yarlagadda, TM D’Alfonso, MG Hanna, A Grabenstetter, ...
Computerized Medical Imaging and Graphics 88, 101866, 2021
Independent real‐world application of a clinical‐grade automated prostate cancer detection system
LM da Silva, EM Pereira, PGO Salles, R Godrich, R Ceballos, JD Kunz, ...
The Journal of pathology 254 (2), 147-158, 2021
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