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Spatial transcriptomics enables interrogating the molecular composition of tissue with ever-increasing resolution and sensitivity.
“Identification of GATA3 as a Breast Cancer Prognostic Marker by Global Gene Expression Meta-analysis”
Rohit Mehra et al · 2005
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“FOXA1 expression in breast cancer—correlation with luminal subtype A and survival”
Sunil Badve et al · 2007
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“FOXA1: Growth inhibitor and a favorable prognostic factor in human breast cancer”
Ido Wolf et al · 2007
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“Imagenet: A large-scale hierarchical image database”
Jia Deng et al · 2009
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“Targeting filamin B induces tumor growth and metastasis via enhanced activity of matrix metalloproteinase-9 and secretion of VEGF-A”
S Bandaru et al · 2014
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“A Dataset for Breast Cancer Histopathological Image Classification”
Fabio. Spanhol, Luiz. Oliveira, Caroline Petitjean and Laurent Heutte · 2015
Earlier work this paper cites.
“Deep residual learning for image recognition”
Kaiming He, Xiangyu Zhang, Shaoqing Ren and Jian Sun · 2016
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“You Only Look Once: Unified, Real-Time Object Detection”
Joseph Redmon, Santosh Divvala, Ross Girshick and Ali Farhadi · 2016
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“Visualization and analysis of gene expression in tissue sections by spatial transcriptomics”
Patrik Sthl et al · 2016
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“Visualization and analysis of gene expression in tissue sections by spatial transcriptomics”
Patrik. Sthl et al · 2016
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“QuPath: Open source software for digital pathology image analysis”
Peter Bankhead et al · 2017
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“Diagnostic assessment of deep learning algorithms for detection of lymph node metastases in women with breast cancer”
Babak Bejnordi et al · 2017
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“Rethinking Atrous Convolution for Semantic Image Segmentation”
Liang-Chieh Chen, George Papandreou, Florian Schroff and Hartwig Adam · 2017
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“Integrating single-cell transcriptomic data across different conditions, technologies, and species”
Andrew Butler et al · 2018
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“Batch effects in single-cell RNA-sequencing data are corrected by matching mutual nearest neighbors”
Laleh Haghverdi, Aaron T.. Lun, Michael. Morgan and John. Marioni · 2018
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“Attention-based Deep Multiple Instance Learning”
Maximilian Ilse, Jakub Tomczak and Max Welling · 2018
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“Representation learning with contrastive predictive coding”
Aaron van Oord, Yazhe Li and Oriol Vinyals · 2018
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“Rotation Equivariant CNNs for Digital Pathology”, 2018
Bastiaan Veeling et al · 2018
Earlier work this paper cites.
“SCANPY: large-scale single-cell gene expression data analysis”
F. Wolf, Philipp Angerer and Fabian. Theis · 2018
Earlier work this paper cites.
“Bach: Grand challenge on breast cancer histology images”
Guilherme Aresta et al · 2019
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“A Spatiotemporal Organ-Wide Gene Expression and Cell Atlas of the Developing Human Heart”
Michaela Asp et al · 2019
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“PanNuke: an open pan-cancer histology dataset for nuclei instance segmentation and classification”
Jevgenij Gamper et al · 2019
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“Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer”
Jakob Kather et al · 2019
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“Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study”
Jakob Kather et al · 2019
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“Fast, sensitive and accurate integration of single-cell data with Harmony”
Ilya Korsunsky et al · 2019
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“Spatiotemporal dynamics of molecular pathology in amyotrophic lateral sclerosis”
Silas Maniatis et al · 2019
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“Predicting EGFR mutation status in lung adenocarcinoma on computed tomography image using deep learning”
Shuo Wang et al · 2019
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“Spatially Resolved Transcriptomes—Next Generation Tools for Tissue Exploration”
Michaela Asp, Joseph Bergenstrhle and Joakim Lundeberg · 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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“Pan-cancer computational histopathology reveals mutations, tumor composition and prognosis”
Yu Fu et al · 2020
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“PanNuke Dataset Extension, Insights and Baselines”
Jevgenij Gamper et al · 2020
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“Integrating spatial gene expression and breast tumour morphology via deep learning”
Bryan He et al · 2020
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“Multimodal Analysis of Composition and Spatial Architecture in Human Squamous Cell Carcinoma”
Andrew. Ji et al · 2020
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“Pan-cancer image-based detection of clinically actionable genetic alterations”
Jakob Kather et al · 2020
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“Big Transfer (BiT): General Visual Representation Learning”
Alexander Kolesnikov et al · 2020
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“Data Efficient and Weakly Supervised Computational Pathology on Whole Slide Images”
Ming Lu et al · 2020
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“Molecular atlas of the adult mouse brain”
Cantin Ortiz et al · 2020
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“A deep learning model to predict RNA-Seq expression of tumours from whole slide images”
Beno\ˆt Schmauch et al · 2020
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“Going deeper through the Gleason scoring scale: An automatic end-to-end system for histology prostate grading and cribriform pattern detection”
Julio Silva-Rodr\’guez et al · 2020
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“Tumor microenvironment as a therapeutic target in cancer”
Yi Xiao and Dihua Yu · 2020
Earlier work this paper cites.
“ComBat-seq: batch effect adjustment for RNA-seq count data”
Yuqing Zhang, Giovanni Parmigiani and W. Johnson · 2020
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“Human squamous cell carcinoma, Visium”
Xes\’us Abalo et al · 2021
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“Spatial deconvolution of HER2-positive breast cancer delineates tumor-associated cell type interactions”
Alma Andersson et al · 2021
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“UniToPatho, a labeled histopathological dataset for colorectal polyps classification and adenoma dysplasia grading”
Carlo Barbano et al · 2021
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“BRACS: A Dataset for BReAst Carcinoma Subtyping in H&E Histology Images”
Nadia Brancati et al · 2021
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“An Empirical Study of Training Self-Supervised Vision Transformers”
Xinlei Chen, Saining Xie and Kaiming He · 2021
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“An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale”
Alexey Dosovitskiy et al · 2021
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“Deep learning in cancer pathology: a new generation of clinical biomarkers”
Amelie Echle et al · 2021
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“Integration of spatial and single-cell transcriptomics localizes epithelial cell–immune cross-talk in kidney injury”
Ricardo Ferreira et al · 2021
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“Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles”
Jevgenij Gamper and Nasir Rajpoot · 2021
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“An N-Cadherin 2 expressing epithelial cell subpopulation predicts response to surgery, chemotherapy and immunotherapy in bladder cancer”
K.. Gouin, N. Ing, J.. Plummer and C.. Rosser · 2021
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“Genome-wide spatial expression profiling in formalin-fixed tissues”
Eva Gracia et al · 2021
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“SpaGCN: Integrating gene expression, spatial location and histology to identify spatial domains and spatially variable genes by graph convolutional network”
Jian Hu et al · 2021
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“Self-Path: Self-supervision for Classification of Pathology Images with Limited Annotations”
Navid Koohbanani et al · 2021
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“From bulk, single-cell to spatial RNA sequencing”
Xinmin Li and Cun-Yu Wang · 2021
Cited alongside, same era.
“Swin transformer: Hierarchical vision transformer using shifted windows”
Ze Liu et al · 2021
Cited alongside, same era.
“AI-based pathology predicts origins for cancers of unknown primary”
Ming Lu et al · 2021
Cited alongside, same era.
“Data-efficient and weakly supervised computational pathology on whole-slide images”
Ming Lu et al · 2021
Cited alongside, same era.
“Method of the Year: spatially resolved transcriptomics”
Vivien Marx · 2021
Cited alongside, same era.
“Transcriptome-scale spatial gene expression in the human dorsolateral prefrontal cortex”
Kristen Maynard et al · 2021
Cited alongside, same era.
“Spatial transcriptomic analysis delineates epithelial and mesenchymal subpopulations and transition stages in childhood ependymoma”
R. Fu, G.. Norris, N. Willard and A.. Griesinger · 2023
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“Rankme: Assessing the downstream performance of pretrained self-supervised representations by their rank”
Quentin Garrido, Randall Balestriero, Laurent Najman and Yann Lecun · 2023
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“Virtual alignment of pathology image series for multi-gigapixel whole slide images”
Chandler. Gatenbee et al · 2023
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“Molecular cartography uncovers evolutionary and microenvironmental dynamics in sporadic colorectal tumors” Publisher: Elsevier
Cody. Heiser et al · 2023
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“A visual–language foundation model for pathology image analysis using medical Twitter”
Zhi Huang et al · 2023
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“Large-scale integration of single-cell transcriptomic data captures transitional progenitor states in mouse skeletal muscle regeneration”
D.. McKellar, L.. Walter, L.. Song and M. Mantri · 2021
Cited alongside, same era.
“Human ileum, Visium”
Reza Mirzazadeh et al · 2021
Cited alongside, same era.
“Leveraging information in spatial transcriptomics to predict super-resolution gene expression from histology images in tumors”
Minxing Pang, Kenong Su and Mingyao Li · 2021
Cited alongside, same era.
“Exploring tissue architecture using spatial transcriptomics”
Anjali Rao, Dalia Barkley, Gustavo. Francca and Itai Yanai · 2021
Cited alongside, same era.
“Tumor protein D52 promotes breast cancer proliferation and migration via the long non-coding RNA NEAT1/microRNA-218-5p axis”
Jing Ren et al · 2021
Cited alongside, same era.
“Transmil: Transformer based correlated multiple instance learning for whole slide image classification”
Zhuchen Shao et al · 2021
Cited alongside, same era.
“High resolution mapping of the tumor microenvironment using integrated single-cell, spatial and in situ analysis”
Amanda Janesick et al · 2023
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“Spatially resolved multiomics of human cardiac niches”
Kazumasa Kanemaru et al · 2023
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“Benchmarking Self-Supervised Learning on Diverse Pathology Datasets”
Mingu Kang et al · 2023
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“Single-cell and spatial transcriptomics reveal aberrant lymphoid developmental programs driving granuloma formation”
Thomas Krausgruber et al · 2023
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“An atlas of healthy and injured cell states and niches in the human kidney”
Blue. Lake et al · 2023
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“Single-nucleus ribonucleic acid-sequencing and spatial transcriptomics reveal the cardioprotection of Shexiang Baoxin Pill (SBP) in mice with myocardial ischemia-reperfusion injury”
Wenyong Lin et al · 2023
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“Visual Language Pretrained Multiple Instance Zero-Shot Transfer for Histopathology Images”
Ming. Lu et al · 2023
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“A spatially resolved atlas of the human lung characterizes a gland-associated immune niche”
Elo Madissoon et al · 2023
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“Spatial mapping of the total transcriptome by in situ polyadenylation”
David. McKellar et al · 2023
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“Spatially resolved transcriptomic profiling of degraded and challenging fresh frozen samples”
Reza Mirzazadeh et al · 2023
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“Spatial Transcriptomics Identifies Expression Signatures Specific to Lacrimal Gland Adenoid Cystic Carcinoma Cells”
Acadia H.. Moeyersoms et al · 2023
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“hist2RNA: An Efficient Deep Learning Architecture to Predict Gene Expression from Breast Cancer Histopathology Images”
Raktim Mondol et al · 2023
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“Dinov2: Learning robust visual features without supervision”
Maxime Oquab et al · 2023
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“Robust mapping of spatiotemporal trajectories and cell–cell interactions in healthy and diseased tissues”
Duy Pham et al · 2023
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“Preneoplastic liver colonization by 11p15.5 altered mosaic cells in young children with hepatoblastoma”
Jill Pilet et al · 2023
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“Breast cancer histopathology image-based gene expression prediction using spatial transcriptomics data and deep learning”
Md Rahaman, Ewan K.. Millar and Erik Meijering · 2023
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“Self-supervised attention-based deep learning for pan-cancer mutation prediction from histopathology”
Oliver Saldanha et al · 2023
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“Artificial intelligence for digital and computational pathology”
Andrew. Song et al · 2023
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“Charting the Heterogeneity of Colorectal Cancer Consensus Molecular Subtypes using Spatial Transcriptomics”
Alberto Valdeolivas et al · 2023
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“Image-based spatial transcriptomics identifies molecular niche dysregulation associated with distal lung remodeling in pulmonary fibrosis”
Annika Vannan et al · 2023
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“Spatial multimodal analysis of transcriptomes and metabolomes in tissues”
Marco Vicari et al · 2023
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“The evolving tumor microenvironment: From cancer initiation to metastatic outgrowth”
Karin. de Visser and Johanna. Joyce · 2023
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“Gene Expression Within a Human Choroidal Neovascular Membrane Using Spatial Transcriptomics”
Andrew. Voigt et al · 2023
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“Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study”
Sophia. Wagner et al · 2023
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“Spatially Resolved Gene Expression Prediction from Histology Images via Bi-modal Contrastive Learning”
Ronald Xie et al · 2023
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“Schwann cells regulate tumor cells and cancer-associated fibroblasts in the pancreatic ductal adenocarcinoma microenvironment”
Meilin Xue et al · 2023
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“Sopa: a technology-invariant pipeline for analyses of image-based spatial omics” Publisher: Nature Publishing Group
Quentin Blampey et al · 2024
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“Towards a General-Purpose Foundation Model for Computational Pathology”
Richard. Chen et al · 2024
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“Accurate Spatial Gene Expression Prediction by integrating Multi-resolution features”
Youngmin Chung, Ji Ha, Kyeong Im and Joo Lee · 2024
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In Zenodo , 2024
“Demo 10x Visium dataset for STQ” [Online; accessed 16. May 2024] · 2024
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“Regression-based Deep-Learning predicts molecular biomarkers from pathology slides”
Omar El et al · 2024
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“CellViT: Vision Transformers for precise cell segmentation and classification”
Fabian Hörst et al · 2024
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“Multistain Pretraining for Slide Representation Learning in Pathology”
Guillaume Jaume et al · 2024
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“Transcriptomics-guided Slide Representation Learning in Computational Pathology”
Guillaume Jaume et al · 2024
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“DiagSet: a dataset for prostate cancer histopathological image classification”
Micha Koziarski et al · 2024
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“YAP induces a neonatal-like pro-renewal niche in the adult heart”
Rich Li et al · 2024
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“A Multimodal Generative AI Copilot for Human Pathology”
Ming. Lu et al · 2024
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“A visual-language foundation model for computational pathology”
Ming Lu et al · 2024
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“SpatialData: an open and universal data framework for spatial omics”
Luca Marconato et al · 2024
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“Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling”
Michelli. Oliveira et al · 2024
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“Distinct mesenchymal cell states mediate prostate cancer progression”
Hubert Pakula et al · 2024
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In Zenodo , 2024
“Spotiphy: generative modeling in single-cell spatial whole transcriptomics” [Online; accessed 16. May 2024] · 2024
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“A foundation model for clinical-grade computational pathology and rare cancers detection”
Eugene Vorontsov et al · 2024
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“M2ORT: Many-To-One Regression Transformer for Spatial Transcriptomics Prediction from Histopathology Images”
Hongyi Wang et al · 2024
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“A whole-slide foundation model for digital pathology from real-world data”
Hanwen Xu et al · 2024
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“Inferring super-resolution tissue architecture by integrating spatial transcriptomics with histology”
Daiwei Zhang et al · 2024
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“Hist2Cell: Deciphering Fine-grained Cellular Architectures from Histology Images”
Weiqin Zhao et al · 2024
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“Virchow2: Scaling Self-Supervised Mixed Magnification Models in Pathology”, 2024
Eric Zimmermann et al · 2024
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