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Recent advances in computational pathology and artificial intelligence have significantly enhanced the utilization of gigapixel whole-slide images and and additional modalities (e.g., genomics) for pathological diagnosis.
Theory of partial likelihood
Wing Hung Wong · 1986
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Review the cancer genome atlas (tcga): an immeasurable source of knowledge
Katarzyna Tomczak, Patrycja Czerwińska, and Maciej Wiznerowicz · 2015
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Self-normalizing neural networks
Günter Klambauer, Thomas Unterthiner, Andreas Mayr, and Sepp Hochreiter · 2017
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Attention-based deep multiple instance learning
Maximilian Ilse, Jakub Tomczak, and Max Welling · 2018
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Predicting cancer outcomes from histology and genomics using convolutional networks
Pooya Mobadersany, Safoora Yousefi, Mohamed Amgad, David A Gutman, Jill S Barnholtz-Sloan, José E Velázquez Vega, Daniel J Brat, and Lee AD Cooper · 2018
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Computing receptive fields of convolutional neural networks
André Araujo, Wade Norris, and Jack Sim · 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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Predicting breast tumor proliferation from whole-slide images: the tupac16 challenge
Mitko Veta, Yujing J Heng, Nikolas Stathonikos, Babak Ehteshami Bejnordi, Francisco Beca, Thomas Wollmann, Karl Rohr, Manan A Shah, Dayong Wang, Mikael Rousson, et al · 2019
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Gene2vec: distributed representation of genes based on co-expression
Jingcheng Du, Peilin Jia, Yulin Dai, Cui Tao, Zhongming Zhao, and Degui Zhi · 2019
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Multiple instance learning with center embeddings for histopathology classification
Philip Chikontwe, Meejeong Kim, Soo Jeong Nam, Heounjeong Go, and Sang Hyun Park · 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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A deep learning model to predict rna-seq expression of tumours from whole slide images
Benoît Schmauch, Alberto Romagnoni, Elodie Pronier, Charlie Saillard, Pascale Maillé, Julien Calderaro, Aurélie Kamoun, Meriem Sefta, Sylvain Toldo, Mikhail Zaslavskiy, et al · 2020
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Biobert: a pre-trained biomedical language representation model for biomedical text mining
Jinhyuk Lee, Wonjin Yoon, Sungdong Kim, Donghyeon Kim, Sunkyu Kim, Chan Ho So, and Jaewoo Kang · 2020
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Bias in cross-entropy-based training of deep survival networks
Shekoufeh Gorgi Zadeh and Matthias Schmid · 2020
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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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Deep learning in histopathology: the path to the clinic
Jeroen Van der Laak, Geert Litjens, and Francesco Ciompi · 2021
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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 · 2021
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Transmil: Transformer based correlated multiple instance learning for whole slide image classification
Zhuchen Shao, Hao Bian, Yang Chen, Yifeng Wang, Jian Zhang, Xiangyang Ji, et al · 2021
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Dt-mil: deformable transformer for multi-instance learning on histopathological image
Hang Li, Fan Yang, Yu Zhao, Xiaohan Xing, Jun Zhang, Mingxuan Gao, Junzhou Huang, Liansheng Wang, and Jianhua Yao · 2021
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Joint analysis of expression levels and histological images identifies genes associated with tissue morphology
Jordan T Ash, Gregory Darnell, Daniel Munro, and Barbara E Engelhardt · 2021
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Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 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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Dsnet: A dual-stream framework for weakly-supervised gigapixel pathology image analysis
Tiange Xiang, Yang Song, Chaoyi Zhang, Dongnan Liu, Mei Chen, Fan Zhang, Heng Huang, Lauren O’Donnell, and Weidong Cai · 2022
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A graph-transformer for whole slide image classification
Yi Zheng, Rushin H Gindra, Emily J Green, Eric J Burks, Margrit Betke, Jennifer E Beane, and Vijaya B Kolachalama · 2022
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Dtfd-mil: Double-tier feature distillation multiple instance learning for histopathology whole slide image classification
Hongrun Zhang, Yanda Meng, Yitian Zhao, Yihong Qiao, Xiaoyun Yang, Sarah E Coupland, and Yalin Zheng · 2022
Cited alongside, same era.
Scl-wc: Cross-slide contrastive learning for weakly-supervised whole-slide image classification
Xiyue Wang, Jinxi Xiang, Jun Zhang, Sen Yang, Zhongyi Yang, Ming-Hui Wang, Jing Zhang, Wei Yang, Junzhou Huang, and Xiao Han · 2022
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Harnessing multimodal data integration to advance precision oncology
Kevin M Boehm, Pegah Khosravi, Rami Vanguri, Jianjiong Gao, and Sohrab P Shah · 2022
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Pan-cancer integrative histology-genomic analysis via multimodal deep learning
Richard J Chen, Ming Y Lu, Drew FK Williamson, Tiffany Y Chen, Jana Lipkova, Zahra Noor, Muhammad Shaban, Maha Shady, Mane Williams, Bumjin Joo, et al · 2022
Towards a generalizable pathology foundation model via unified knowledge distillation
Jiabo Ma, Zhengrui Guo, Fengtao Zhou, Yihui Wang, Yingxue Xu, Yu Cai, Zhengjie Zhu, Cheng Jin, Yi Lin Xinrui Jiang, Anjia Han, et al · 2024
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Transcriptomics-guided slide representation learning in computational pathology
Guillaume Jaume, Lukas Oldenburg, Anurag Vaidya, Richard J. Chen, Drew F.K. Williamson, Thomas Peeters, Andrew H. Song, and Faisal Mahmood · 2024
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A multimodal knowledge-enhanced whole-slide pathology foundation model
Yingxue Xu, Yihui Wang, Fengtao Zhou, Jiabo Ma, Shu Yang, Huangjing Lin, Xin Wang, Jiguang Wang, Li Liang, Anjia Han, et al · 2024
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Modeling dense multimodal interactions between biological pathways and histology for survival prediction
Guillaume Jaume, Anurag Vaidya, Richard J. Chen, Drew F.K. Williamson, Paul Pu Liang, and Faisal Mahmood · 2024
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Hfbsurv: hierarchical multimodal fusion with factorized bilinear models for cancer survival prediction
Ruiqing Li, Xingqi Wu, Ao Li, and Minghui Wang · 2022
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Scaling vision transformers to gigapixel images via hierarchical self-supervised learning
Richard J Chen, Chengkuan Chen, Yicong Li, Tiffany Y Chen, Andrew D Trister, Rahul G Krishnan, and Faisal Mahmood · 2022
Cited alongside, same era.
scbert as a large-scale pretrained deep language model for cell type annotation of single-cell rna-seq data
Fan Yang, Wenchuan Wang, Fang Wang, Yuan Fang, Duyu Tang, Junzhou Huang, Hui Lu, and Jianhua Yao · 2022
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Bracs: A dataset for breast carcinoma subtyping in h&e histology images
Nadia Brancati, Anna Maria Anniciello, Pushpak Pati, Daniel Riccio, Giosuè Scognamiglio, Guillaume Jaume, Giuseppe De Pietro, Maurizio Di Bonito, Antonio Foncubierta, Gerardo Botti, et al · 2022
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Artificial intelligence for diagnosis and gleason grading of prostate cancer: the panda challenge
Wouter Bulten, Kimmo Kartasalo, Po-Hsuan Cameron Chen, Peter Ström, Hans Pinckaers, Kunal Nagpal, Yuannan Cai, David F Steiner, Hester Van Boven, Robert Vink, et al · 2022
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Inference of captions from histopathological patches, 2022
Masayuki Tsuneki and Fahdi Kanavati · 2022
Cited alongside, same era.
Healnet–hybrid multi-modal fusion for heterogeneous biomedical data
Konstantin Hemker, Nikola Simidjievski, and Mateja Jamnik · 2023
Cited alongside, same era.
Richard J Chen, Tong Ding, Ming Y Lu, Drew FK Williamson, Guillaume Jaume, Andrew H Song, Bowen Chen, Andrew Zhang, Daniel Shao, Muhammad Shaban, et al · 2024
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Dynamic graph representation with knowledge-aware attention for histopathology whole slide image analysis
Jiawen Li, Yuxuan Chen, Hongbo Chu, Qiehe Sun, Tian Guan, Anjia Han, and Yonghong He · 2024
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Mambamil: Enhancing long sequence modeling with sequence reordering in computational pathology
Shu Yang, Yihui Wang, and Hao Chen · 2024
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Modeling dense multimodal interactions between biological pathways and histology for survival prediction
Guillaume Jaume, Anurag Vaidya, Richard J Chen, Drew FK Williamson, Paul Pu Liang, and Faisal Mahmood · 2024
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Spatially resolved gene expression prediction from histology images via bi-modal contrastive learning
Ronald Xie, Kuan Pang, Sai Chung, Catia Perciani, Sonya MacParland, Bo Wang, and Gary Bader · 2024
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Genomics-guided representation learning for pathologic pan-cancer tumor microenvironment subtype prediction
Fangliangzi Meng, Hongrun Zhang, Ruodan Yan, Guohui Chuai, Chao Li, and Qi Liu · 2024
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Healnet: Multimodal fusion for heterogeneous biomedical data
Konstantin Hemker, Nikola Simidjievski, and Mateja Jamnik · 2024
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Histgen: Histopathology report generation via local-global feature encoding and cross-modal context interaction
Zhengrui Guo, Jiabo Ma, Yingxue Xu, Yihui Wang, Liansheng Wang, and Hao Chen · 2024
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Masked pre-training of transformers for histology image analysis
Shuai Jiang, Liesbeth Hondelink, Arief A Suriawinata, and Saeed Hassanpour · 2024
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Morphological prototyping for unsupervised slide representation learning in computational pathology
Andrew H Song, Richard J Chen, Tong Ding, Drew FK Williamson, Guillaume Jaume, and Faisal Mahmood · 2024
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Transcriptomics-guided slide representation learning in computational pathology
Guillaume Jaume, Lukas Oldenburg, Anurag Vaidya, Richard J Chen, Drew FK Williamson, Thomas Peeters, Andrew H Song, and Faisal Mahmood · 2024
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Multistain pretraining for slide representation learning in pathology
Guillaume Jaume, Anurag Vaidya, Andrew Zhang, Andrew H Song, Richard J Chen, Sharifa Sahai, Dandan Mo, Emilio Madrigal, Long Phi Le, and Faisal Mahmood · 2024
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A whole-slide foundation model for digital pathology from real-world data
Hanwen Xu, Naoto Usuyama, Jaspreet Bagga, Sheng Zhang, Rajesh Rao, Tristan Naumann, Cliff Wong, Zelalem Gero, Javier González, Yu Gu, et al · 2024
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A foundation model for clinical-grade computational pathology and rare cancers detection
Eugene Vorontsov, Alican Bozkurt, Adam Casson, George Shaikovski, Michal Zelechowski, Kristen Severson, Eric Zimmermann, James Hall, Neil Tenenholtz, Nicolo Fusi, et al · 2024
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A pathology foundation model for cancer diagnosis and prognosis prediction
Xiyue Wang, Junhan Zhao, Eliana Marostica, Wei Yuan, Jietian Jin, Jiayu Zhang, Ruijiang Li, Hongping Tang, Kanran Wang, Yu Li, et al · 2024
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A visual-language foundation model for computational pathology
Ming Y Lu, Bowen Chen, Drew FK Williamson, Richard J Chen, Ivy Liang, Tong Ding, Guillaume Jaume, Igor Odintsov, Long Phi Le, Georg Gerber, et al · 2024
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Prototypical information bottlenecking and disentangling for multimodal cancer survival prediction
Yilan Zhang, Yingxue Xu, Jianqi Chen, Fengying Xie, and Hao Chen · 2024
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Machine learning-driven histotype diagnosis of ovarian carcinoma: insights from the ocean ai challenge
Maryam Asadi-Aghbolaghi, Hossein Farahani, Allen Zhang, Ardalan Akbari, Sirim Kim, Ashley Chow, Sohier Dane, OCEAN Challenge Consortium, OTTA Consortium, David G Huntsman, et al · 2024
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Wsicaption: Multiple instance generation of pathology reports for gigapixel whole-slide images
Pingyi Chen, Honglin Li, Chenglu Zhu, Sunyi Zheng, Zhongyi Shui, and Lin Yang · 2024
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Lung cancer in patients who have never smoked—an emerging disease
Jaclyn LoPiccolo, Alexander Gusev, David C Christiani, and Pasi A Jänne · 2024
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