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
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
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
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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