A practical guide to whole slide imaging: a white paper from the digital pathology association, Arch. Pathol. Lab. Med, vol.143, pp.222-234, 2019. ,
Whole slide imaging versus microscopy for primary diagnosis in surgical pathology: a multicenter blinded randomized noninferiority study of 1992 cases (pivotal study), Am. J. Surg. Pathol, vol.42, pp.39-52, 2018. ,
Mitosis detection in breast cancer pathology images by combining handcrafted and convolutional neural network features, J. Med. Imaging Bellingham Wash, vol.1, p.34003, 2014. ,
Antibodysupervised deep learning for quantification of tumor-infiltrating immune cells in hematoxylin and eosin stained breast cancer samples, J. Pathol. Inform, vol.7, p.38, 2016. ,
Patch-based convolutional neural network for whole slide tissue image classification, Proc. IEEE Comput. Soc. Conf. Comput. Vis. Pattern Recognit, pp.2424-2433, 2016. ,
Automated deep-learning system for Gleason grading of prostate cancer using biopsies: a diagnostic study, Lancet Oncol, vol.21, pp.233-241, 2020. ,
And they said it couldn't be done: predicting known driver mutations from H&E slides, J. Pathol. Inform, vol.10, p.17, 2019. ,
Classification and mutation prediction from non-small cell lung cancer histopathology images using deep learning, Nat. Med, vol.24, pp.1559-1567, 2018. ,
Predicting cancer outcomes from histology and genomics using convolutional networks, Proc. Natl Acad. Sci. USA, vol.115, pp.2970-2979, 2018. ,
H&E-stained whole slide image deep learning predicts SPOP mutation state in prostate cancer, 2018. ,
Deep-learning convolutional neural networks accurately classify genetic mutations in gliomas, Am. J. Neuroradiol, vol.39, pp.1201-1207, 2018. ,
Pan-cancer classifications of tumor histological images using deep learning, 2020. ,
Using transfer learning on whole slide images to predict tumor mutational burden in bladder cancer patients, Bioinformatics, 2019. ,
From signatures to models: understanding cancer using microarrays, Nat. Genet, vol.37, pp.38-45, 2005. ,
Array of hope, Nat. Genet, vol.21, pp.3-4, 1999. ,
A survey of best practices for RNA-seq data analysis, Genome Biol, vol.17, p.13, 2016. ,
Differential expression analysis for sequence count data, Genome Biol, vol.11, p.106, 2010. ,
Next-generation sequencing: advances and applications in cancer diagnosis, OncoTargets Ther, vol.9, pp.7355-7365, 2016. ,
The cancer genome, Nature, vol.458, pp.719-724, 2009. ,
Next-generation sequencing in oncology: genetic diagnosis, risk prediction and cancer classification, Int. J. Mol. Sci, vol.18, p.308, 2017. ,
Cell-type-specific gene expression profiling in adult mouse brain reveals normal and disease-state signatures, Cell Rep, vol.26, pp.2477-2493, 2019. ,
URL : https://hal.archives-ouvertes.fr/hal-02087719
Systematic exploration of cell morphological phenotypes associated with a transcriptomic query, Nucleic Acids Res, vol.46, pp.116-116, 2018. ,
Genomics and the continuum of cancer care, N. Engl. J. Med, vol.364, pp.340-350, 2011. ,
Classification and disease localization in histopathology using only global labels: a weaklysupervised approach, 2018. ,
Targeting the complement pathway as a therapeutic strategy in lung cancer, Front. Immunol, vol.10, p.954, 2019. ,
The tetraspanin CD53 modulates responses from activating NK cell receptors, promoting LFA-1 activation and dampening NK cell effector functions, PLoS ONE, vol.9, p.97844, 2014. ,
Characterization of GMP-17, a granule membrane protein that moves to the plasma membrane of natural killer cells following target cell recognition, Proc. Natl Acad. Sci. USA, vol.93, pp.685-689, 1996. ,
Molecular link between liver fibrosis and hepatocellular carcinoma, Liver Cancer, vol.2, pp.365-366, 2013. ,
Current perspectives on CHEK2 mutations in breast cancer, Breast Cancer Dove Med. Press, vol.9, pp.331-335, 2017. ,
Association of csk-homologous kinase (CHK) (formerly MATK) with HER-2/ErbB-2 in breast cancer cells, J. Biol. Chem, vol.272, pp.1856-1863, 1997. ,
Cyclins and breast cancer, J. Mammary Gland Biol. Neoplasia, vol.9, pp.95-104, 2004. ,
Hallmarks of cancer: the next generation, Cell, vol.144, pp.646-674, 2011. ,
Virtual histological staining of unlabelled tissueautofluorescence images via deep learning, Nat. Biomed. Eng, vol.3, pp.466-477, 2019. ,
Spatial organization and molecular correlation of tumorinfiltrating lymphocytes using deep learning on pathology images, Cell Rep, vol.23, pp.181-193, 2018. ,
Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study, PLoS Med, vol.16, p.1002730, 2019. ,
000 histological images of human colorectal cancer and healthy tissue (Version v0.1), vol.100, 2018. ,
The prognostic landscape of genes and infiltrating immune cells across human cancers, Nat. Med, vol.21, pp.938-945, 2015. ,
Identification and sequence of a fourth human T cell antigen receptor chain, Nature, vol.330, pp.569-572, 1987. ,
CD19 and CD20 targeted vectors induce minimal activation of resting B lymphocytes, PLoS ONE, vol.8, p.79047, 2013. ,
QuPath: open source software for digital pathology image analysis, Sci. Rep, vol.7, pp.1-7, 2017. ,
Epithelium segmentation using deep learning in H&E-stained prostate specimens with immunohistochemistry as reference standard, Sci. Rep, vol.9, p.864, 2019. ,
PESO: prostate epithelium segmentation on H&E-stained prostatectomy whole slide images (Version 1, 2018. ,
Predicting survival after hepatocellular carcinoma resection using deep-learning on histological slides, Hepatology, 2020. ,
Small hepatocellular carcinoma of single nodular type: a specific reference to its surrounding cancerous area undetected radiologically and macroscopically, J. Surg. Oncol, vol.60, pp.75-79, 1995. ,
Ki-67 antigen expression in hepatocellular carcinoma using monoclonal antibody MIB1. A comparison with proliferating cell nuclear antigen, Am. J. Clin. Pathol, vol.104, p.313, 1995. ,
A long-term survivor of ruptured hepatocellular carcinoma after hepatic resection, J. Gastroenterol. Hepatol, vol.10, p.351, 1995. ,
Clinicopathological and prognostic significance of high Ki-67 labeling index in hepatocellular carcinoma patients: a meta-analysis, Int. J. Clin. Exp. Med, vol.8, pp.10235-10247, 2015. ,
Bruix Prognosis of hepatocellular carcinoma: the BCLC staging classification, J. Semin Liver Dis, vol.19, pp.329-338, 1999. ,
A molecular portrait of microsatellite instability across multiple cancers, Nat. Commun, vol.8, p.15180, 2017. ,
Is there a difference between T-and B-lymphocyte morphology, J. Biomed. Optics, vol.14, p.64036, 2009. ,
Colorectal and other cancer risks for carriers and noncarriers from families with a DNA mismatch repair gene mutation: a prospective cohort study, J. Clin. Oncol, vol.30, pp.958-964, 2012. ,
Microsatellite instability in colorectal cancer, Gastroenterology, vol.138, 2010. ,
Mismatch repair deficiency predicts response of solid tumors to PD-1 blockade, Science, vol.357, pp.409-413, 2017. ,
First FDA approval agnostic of cancer sitewhen a biomarker defines the indication, N. Engl. J. Med, vol.377, pp.1409-1412, 2017. ,
Genomics and emerging biomarkers for immunotherapy of colorectal cancer, Semin. Cancer Biol, vol.52, pp.189-197, 2018. ,
Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer, Nat. Med, vol.25, pp.1054-1056, 2019. ,
Systematic analysis of breast cancer morphology uncovers stromal features associated with survival, Sci. Transl. Med, vol.3, pp.108-113, 2011. ,
Quantitative nuclear histomorphometry predicts oncotype DX risk categories for early stage ER+ breast cancer, BMC Cancer, vol.18, p.610, 2018. ,
Correlating nuclear morphometric patterns with estrogen receptor status in breast cancer pathologic specimens, Breast Cancer, vol.4, p.32, 2018. ,
Integrated analysis of transcriptomic and proteomic data, Curr. Genomics, vol.2, pp.91-110, 2013. ,
Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2, Genome Biol, vol.15, p.550, 2014. ,
A threshold selection method from gray-level histograms, IEEE Trans. Syst., man, Cybern, vol.9, pp.62-66, 1979. ,
Deep residual learning for image recognition, Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pp.770-778, 2016. ,
Imagenet: a large-scale hierarchical image database, 2009 IEEE Conference on Computer Vision and Pattern Recognition, pp.248-255, 2009. ,
SLIC superpixels compared to state-of-the-art superpixel methods, IEEE Trans. Pattern Anal. Mach. Intell, vol.34, pp.2274-2282, 2022. ,
TCGAbiolinks: an R/Bioconductor package for integrative analysis of TCGA data, Nucleic Acids Res, vol.44, pp.71-71, 2016. ,
A National Cancer Institute Workshop on Microsatellite Instability for cancer detection and familial predisposition: development of international criteria for the determination of microsatellite instability in colorectal cancer, Cancer Res, vol.58, pp.5248-5257, 1998. ,
, Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer, Nature, vol.487, p.330, 2012.
Understanding deep neural networks with rectified linear units, 2016. ,