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Tissue phenotyping is a fundamental task in learning objective characterizations of histopathologic biomarkers within the tumor-immune microenvironment in cancer pathology.
Representing part-whole hierarchies in connectionist networks
Geoffrey E Hinton · 1988
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Accuracy of biopsy gleason scores from a large uropathology laboratory: use of a diagnostic protocol to minimize observer variability
Grant D Carlson, Christina B Calvanese, Hillel Kahane, and Jonathan I Epstein · 1998
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Reproducibility of the who/iaslc grading system for pre-invasive squamous lesions of the bronchus: a study of inter-observer and intra-observer variation
AG Nicholson, LJ Perry, PM Cury, P Jackson, CM McCormick, B Corrin, and AU Wells · 2001
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Biomarkers in cancer staging, prognosis and treatment selection
Joseph A Ludwig and John N Weinstein · 2005
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Grading systems in renal cell carcinoma
Giacomo Novara, Guido Martignoni, Walter Artibani, and Vincenzo Ficarra · 2007
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Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
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Classification of tumor histology via morphometric context
Hang Chang, Alexander Borowsky, Paul Spellman, and Bahram Parvin · 2013
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Multi-class texture analysis in colorectal cancer histology
Jakob Nikolas Kather, Cleo-Aron Weis, Francesco Bianconi, Susanne M Melchers, Lothar R Schad, Timo Gaiser, Alexander Marx, and Frank Gerrit Zöllner · 2016
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Harrison Edwards and Amos Storkey · 2016
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The eighth edition ajcc cancer staging manual: continuing to build a bridge from a population-based to a more “personalized” approach to cancer staging
Mahul B Amin, Frederick L Greene, Stephen B Edge, Carolyn C Compton, Jeffrey E Gershenwald, Robert K Brookland, Laura Meyer, Donna M Gress, David R Byrd, and David P Winchester · 2017
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Lukasz Kaiser, and Illia Polosukhin · 2017
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Deep sets
Manzil Zaheer, Satwik Kottur, Siamak Ravanbakhsh, Barnabas Poczos, Ruslan Salakhutdinov, and Alexander Smola · 2017
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
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Attention-based deep multiple instance learning
Maximilian Ilse, Jakub Tomczak, and Max Welling · 2018
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Spatial organization and molecular correlation of tumor-infiltrating lymphocytes using deep learning on pathology images
Joel Saltz, Rajarsi Gupta, Le Hou, Tahsin Kurc, Pankaj Singh, Vu Nguyen, Dimitris Samaras, Kenneth R Shroyer, Tianhao Zhao, Rebecca Batiste, et al · 2018
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Interobserver variability in breast carcinoma grading results in prognostic stage differences
Kimmie Rabe, Olivia L Snir, Veerle Bossuyt, Malini Harigopal, Romulo Celli, and Emily S Reisenbichler · 2019
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Clinical-grade computational pathology using weakly supervised deep learning on whole slide images
Gabriele Campanella, Matthew G Hanna, Luke Geneslaw, Allen Miraflor, Vitor Werneck Krauss Silva, Klaus J Busam, Edi Brogi, Victor E Reuter, David S Klimstra, and Thomas J Fuchs · 2019
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Semi-supervised histology classification using deep multiple instance learning and contrastive predictive coding
Ming Y Lu, Richard J Chen, Jingwen Wang, Debora Dillon, and Faisal Mahmood · 2019
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Large scale adversarial representation learning
Jeff Donahue and Karen Simonyan · 2019
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Structured crowdsourcing enables convolutional segmentation of histology images
Mohamed Amgad, Habiba Elfandy, Hagar Hussein, Lamees A Atteya, Mai AT Elsebaie, Lamia S Abo Elnasr, Rokia A Sakr, Hazem SE Salem, Ahmed F Ismail, Anas M Saad, et al · 2019
Ching-Yao Chuang, Joshua Robinson, Lin Yen-Chen, Antonio Torralba, and Stefanie Jegelka · 2020
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Mlp-mixer: An all-mlp architecture for vision
Ilya Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, et al · 2021
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Whole slide images are 2d point clouds: Context-aware survival prediction using patch-based graph convolutional networks
Richard J Chen, Ming Y Lu, Muhammad Shaban, Chengkuan Chen, Tiffany Y Chen, Drew FK Williamson, and Faisal Mahmood · 2021
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Multimodal co-attention transformer for survival prediction in gigapixel whole slide images
Richard J Chen, Ming Y Lu, Wei-Hung Weng, Tiffany Y Chen, Drew FK Williamson, Trevor Manz, Maha Shady, and Faisal Mahmood · 2021
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Exploring simple siamese representation learning
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Cellular community detection for tissue phenotyping in colorectal cancer histology images
Sajid Javed, Arif Mahmood, Muhammad Moazam Fraz, Navid Alemi Koohbanani, Ksenija Benes, Yee-Wah Tsang, Katherine Hewitt, David Epstein, David Snead, and Nasir Rajpoot · 2020
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Data efficient and weakly supervised computational pathology on whole slide images
Ming Y Lu, Drew FK Williamson, Tiffany Y Chen, Richard J Chen, Matteo Barbieri, and Faisal Mahmood · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen, Simon Kornblith, Mohammad Norouzi, and Geoffrey Hinton · 2020
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Momentum contrast for unsupervised visual representation learning
Kaiming He, Haoqi Fan, Yuxin Wu, Saining Xie, and Ross Girshick · 2020
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Bootstrap your own latent: A new approach to self-supervised learning
Jean-Bastien Grill, Florian Strub, Florent Altché, Corentin Tallec, Pierre H Richemond, Elena Buchatskaya, Carl Doersch, Bernardo Avila Pires, Zhaohan Daniel Guo, Mohammad Gheshlaghi Azar, et al · 2020
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Weakly supervised prostate tma classification via graph convolutional networks
Jingwen Wang, Richard J Chen, Ming Y Lu, Alexander Baras, and Faisal Mahmood · 2020
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Pathomic fusion: an integrated framework for fusing histopathology and genomic features for cancer diagnosis and prognosis
Richard J Chen, Ming Y Lu, Jingwen Wang, Drew FK Williamson, Scott J Rodig, Neal I Lindeman, and Faisal Mahmood · 2020
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Xinlei Chen and Kaiming He · 2021
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Emerging properties in self-supervised vision transformers
Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021
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Dual-stream multiple instance learning network for whole slide image classification with self-supervised contrastive learning
Bin Li, Yin Li, and Kevin W Eliceiri · 2021
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Self-path: Self-supervision for classification of pathology images with limited annotations
Navid Alemi Koohbanani, Balagopal Unnikrishnan, Syed Ali Khurram, Pavitra Krishnaswamy, and Nasir Rajpoot · 2021
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Resource and data efficient self supervised learning
Ozan Ciga, Tony Xu, and Anne L Martel · 2021
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Self supervised learning improves dmmr/msi detection from histology slides across multiple cancers
Charlie Saillard, Olivier Dehaene, Tanguy Marchand, Olivier Moindrot, Aurélie Kamoun, Benoit Schmauch, and Simon Jegou · 2021
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Adversarial learning of cancer tissue representations
Adalberto Claudio Quiros, Nicolas Coudray, Anna Yeaton, Wisuwat Sunhem, Roderick Murray-Smith, Aristotelis Tsirigos, and Ke Yuan · 2021
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Transpath: Transformer-based self-supervised learning for histopathological image classification
Xiyue Wang, Sen Yang, Jun Zhang, Minghui Wang, Jing Zhang, Junzhou Huang, Wei Yang, and Xiao Han · 2021
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Spie-aapm-nci breastpathq challenge: an image analysis challenge for quantitative tumor cellularity assessment in breast cancer histology images following neoadjuvant treatment
Nicholas Petrick, Shazia Akbar, Kenny H Cha, Sharon Nofech-Mozes, Berkman Sahiner, Marios A Gavrielides, Jayashree Kalpathy-Cramer, Karen Drukker, Anne L Martel, et al · 2021
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Localizing objects with self-supervised transformers and no labels
Oriane Siméoni, Gilles Puy, Huy V Vo, Simon Roburin, Spyros Gidaris, Andrei Bursuc, Patrick Pérez, Renaud Marlet, and Jean Ponce · 2021
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Self-supervised driven consistency training for annotation efficient histopathology image analysis
Chetan L Srinidhi, Seung Wook Kim, Fu-Der Chen, and Anne L Martel · 2022
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