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Deep learning has recently gained popularity in digital pathology due to its high prediction quality.
Computational pathology: Challenges and promises for tissue analysis
Fuchs, T. J. & Buhmann, J. M · 2011
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Visual pattern mining in histology image collections using bag of features
Cruz-Roa, A., Caicedo, J. C. & González, F. A · 2011
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Imagenet classification with deep convolutional neural networks
Krizhevsky, A., Sutskever, I. & Hinton, G. E · 2012
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Quantitative image analysis of cellular heterogeneity in breast tumors complements genomic profiling
Yuan, Y. et al · 2012
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Deep inside convolutional networks: Visualising image classification models and saliency maps
Simonyan, K., Vedaldi, A. & Zisserman, A · 2013
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A deep learning architecture for image representation, visual interpretability and automated basal-cell carcinoma cancer detection
Cruz-Roa, A. A., Ovalle, J. E. A., Madabhushi, A. & Osorio, F. A. G · 2013
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Visualizing and understanding convolutional networks
Zeiler, M. D. & Fergus, R · 2014
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Caffe: Convolutional architecture for fast feature embedding
Jia, Y. et al · 2014
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Deep learning
LeCun, Y., Bengio, Y. & Hinton, G. E · 2015
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Deep learning in neural networks: An overview
Schmidhuber, J · 2015
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Going deeper with convolutions
Szegedy, C. et al · 2015
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U-net: Convolutional networks for biomedical image segmentation
Ronneberger, O., Fischer, P. & Brox, T · 2015
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Understanding neural networks through deep visualization
Yosinski, J., Clune, J., Nguyen, A. M., Fuchs, T. J. & Lipson, H · 2015
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On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Bach, S. et al · 2015
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Deep learning as a tool for increased accuracy and efficiency of histopathological diagnosis
Litjens, G. et al · 2016
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Analyzing classifiers: Fisher vectors and deep neural networks
Lapuschkin, S., Binder, A., Montavon, G., Müller, K.-R. & Samek, W · 2016
Cited alongside, same era.
Locality sensitive deep learning for detection and classification of nuclei in routine colon cancer histology images
Sirinukunwattana, K. et al · 2016
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Stacked sparse autoencoder for nuclei detection on breast cancer histopathology images
Xu, J. et al · 2016
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Deep residual learning for image recognition
He, K., Zhang, X., Ren, S. & Sun, J · 2016
Cited alongside, same era.
Deep learning for identifying metastatic breast cancer
Wang, D., Khosla, A., Gargeya, R., Irshad, H. & Beck, A. H · 2016
Cited alongside, same era.
A survey on deep learning in medical image analysis
Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features
Xu, Y. et al · 2017
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Context-aware stacked convolutional neural networks for classification of breast carcinomas in whole-slide histopathology images
Bejnordi, B. E. et al · 2017
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Detecting cancer metastases on gigapixel pathology images
Liu, Y. et al · 2017
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Understanding and comparing deep neural networks for age and gender classification
Lapuschkin, S., Binder, A., Müller, K.-R. & Samek, W · 2017
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Methods for interpreting and understanding deep neural networks
Montavon, G., Samek, W. & Müller, K.-R · 2017
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Litjens, G. et al · 2017
Cited alongside, same era.
Dermatologist-level classification of skin cancer with deep neural networks
Esteva, A. et al · 2017
Cited alongside, same era.
Grad-CAM: Visual explanations from deep networks via gradient-based localization
Selvaraju, R. R. et al · 2017
Cited alongside, same era.
PatternNet and PatternLRP - improving the interpretability of neural networks
Kindermans, P., Schütt, K. T., Alber, M., Müller, K.-R. & Dähne, S · 2017
Cited alongside, same era.
Explaining nonlinear classification decisions with deep taylor decomposition
Montavon, G., Bach, S., Binder, A., Samek, W. & Müller, K.-R · 2017
Cited alongside, same era.
Visualizing deep neural network decisions: Prediction difference analysis
Zintgraf, L. M., Cohen, T. S., Adel, T. & Welling, M · 2017
Cited alongside, same era.
Looking under the hood: Deep neural network visualization to interpret whole-slide image analysis outcomes for colorectal polyps
Korbar, B. et al · 2017
Cited alongside, same era.
Lapuschkin, S., Binder, A., Montavon, G., Müller, K.-R. & Samek, W · 2017
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Binder, A. et al · 2018
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Deep convolutional neural networks enable discrimination of heterogeneous digital pathology images
Khosravi, P., Kazemi, E., Imielinski, M., Elemento, O. & Hajirasouliha, I · 2018
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Scoring of tumor-infiltrating lymphocytes: From visual estimation to machine learning
Klauschen, F. et al · 2018
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Regression concept vectors for bidirectional explanations in histopathology
Graziani, M., Andrearczyk, V. & Müller, H · 2018
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Predicting cancer outcomes from histology and genomics using convolutional networks
Mobadersany, P. et al · 2018
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Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
Coudray, N. et al · 2018
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Unmasking clever hans predictors and assessing what machines really learn
Lapuschkin, S. et al · 2019
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Innvestigate neural networks!
Alber, M. et al · 2019
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