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Explainability of machine learning (ML) techniques in digital pathology (DP) is of great significance to facilitate their wide adoption in clinics.
GNNExplainer: Generating Explanations for Graph Neural Networks
Ying, R., Bourgeois, D., You, J., Zitnik, M., and Leskovec, J · 1903
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Regression Concept Vectors for Bidirectional Explanations in Histopathology
Graziani, M., Andrearczyk, V., and Müller, H · 1904
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Hägele, M., Seegerer, P., Lapuschkin, S., Bockmayr, M., Samek, W., Klauschen, F., Müller, K.-R., and Binder, A · 1908
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CGC-Net: Cell Graph Convolutional Network for Grading of Colorectal Cancer Histology Images
Zhou, Y., Graham, S., Koohbanani, N. A., Shaban, M., Heng, P.-A., and Rajpoot, N · 1909
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The cell graphs of cancer
Gunduz, C., Yener, B., and Gultekin, S. H · 2004
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LNCS 8150 - A Deep Learning Architecture for Image Representation, Visual Interpretability and Automated Basal-Cell Carcinoma Cancer Detection
Cruz-Roa, A., Ovalle, A. A., John, E., Madabhushi, A., and González Osorio, F. A · 2013
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On pixel-wise explanations for non-linear classifier decisions by layer-wise relevance propagation
Bach, S., Binder, A., Montavon, G., Klauschen, F., Müller, K. R., and Samek, W · 2015
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Distilling the Knowledge in a Neural Network
Hinton, G., Vinyals, O., and Dean, J · 2015
Earlier work this paper cites.
Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering
Defferrard, M., Bresson, X., and Vandergheynst, P · 2016
Cited alongside, same era.
Cell nuclei attributed relational graphs for efficient representation and classification of gastric cancer in digital histopathology
Sharma, H., Zerbe, N., Heim, D., Wienert, S., Lohmann, S., Hellwich, O., and Hufnagl, P · 2016
Cited alongside, same era.
Looking under the hood Deep neural network visualization to interpret whole slide Image analysis outcomes for colorectal polyps
Bruno, K., Andrea, M. O., Allen, P. M., Catherine, M. N., Matthew, A. S., Lorenzo, T., Arief, A. S., and Saeed, H · 2017
Cited alongside, same era.
Neural Message Passing for Quantum Chemistry
Gilmer, J., Schoenholz, S. S., Riley, P. F., Vinyals, O., and Dahl, G. E · 2017
Cited alongside, same era.
Towards the Augmented Pathologist: Challenges of Explainable-AI in Digital Pathology
Veličković, P., Cucurull, G., Casanova, A., Romero, A., Liò, P., and Bengio, Y · 2018
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Histographs: Graphs in histopathology
Gadiya, S., Anand, D., and Sethi, A · 2019
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Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
Graham, S., Vu, Q. D., Raza, S. E. A., Azam, A., Tsang, Y. W., Kwak, J. T., and Rajpoot, N · 2019
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PyTorch: An imperative style, high-performance deep learning library
Paszke, A., Gross, S., Massa, F., Lerer, A., Bradbury, J., Chanan, G., Killeen, T., Lin, Z., Gimelshein, N., Antiga, L., and Others · 2019
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Weakly supervised prostate tma classification via graph convolutional networks
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Holzinger, A., Malle, B., Kieseberg, P., Roth, P. M., Müller, H., Reihs, R., and Zatloukal, K · 2017
Cited alongside, same era.
Semi supervised classification with graph convolutional networks
Kipf, T. N. and Welling, M · 2017
Cited alongside, same era.
Predicting cancer outcomes from histology and genomics using convolutional networks
Mobadersany, P., Yousefi, S., Amgad, M., Gutman, D., Barnholtz-Sloan, J., Velazquez Vega, J. E., Brat, D., and Cooper, L. A · 2017
Cited alongside, same era.
Large scale tissue histopathology image classification, segmentation, and visualization via deep convolutional activation features
Xu, Y., Jia, Z., Wang, L. B., Ai, Y., Zhang, F., Lai, M., and Chang, E. I · 2017
Cited alongside, same era.
Wang, J., Chen, R. J., Lu, M. Y., Baras, A., and Mahmood, F · 2019
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How Powerful are Graph Neural Networks?
Xu, K., Hu, W., Leskovec, J., and Jegelka, S · 2019
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A multi-organ nucleus segmentation challenge
Kumar, N. and et al · 2020
Closest in time.
HACT-Net: A Hierarchical Cell-to-Tissue Graph Neural Network for Histopathological Image Classification
Pati, P., Jaume, G., Alisha Fernandes, L., Foncubierta, A., Feroce, F., Anniciello, A. M., Scognamiglio, G., Brancati, N., Riccio, D., Do Bonito, M., De Pietro, G., Botti, G., Goksel, O., Thiran, J.-P., Frucci, M., and Gabrani, M · 2020
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