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Efficient pan-cancer whole-slide image classification and outlier detection using convolutional neural networks

https://doi.org/10.1101/633123
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Minimizing Computation in Convolutional Neural Networks
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U-Net: Convolutional Networks for Biomedical Image Segmentation
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Histopathological Diagnosis for Viable and Non-viable Tumor Prediction for Osteosarcoma Using Convolutional Neural Network
inferredcites →https://doi.org/10.1016/j.celrep.2018.03.086openalex-snapshot
Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images
inferredcites →https://doi.org/10.1016/j.ebiom.2017.12.026openalex-snapshot
Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images
inferredcites →https://doi.org/10.1016/j.jtho.2016.10.017openalex-snapshot
Comprehensive Computational Pathological Image Analysis Predicts Lung Cancer Prognosis
inferredcites →https://doi.org/10.1016/j.media.2016.06.037openalex-snapshot
Image analysis and machine learning in digital pathology: Challenges and opportunities
inferredcites →https://doi.org/10.1038/nature21056openalex-snapshot
Dermatologist-level classification of skin cancer with deep neural networks
inferredcites →https://doi.org/10.1038/ncomms12474openalex-snapshot
Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features
inferredcites →https://doi.org/10.1038/s41591-018-0177-5openalex-snapshot
Classification and mutation prediction from non–small cell lung cancer histopathology images using deep learning
inferredcites →https://doi.org/10.1038/s41698-017-0022-1openalex-snapshot
Precision histology: how deep learning is poised to revitalize histomorphology for personalized cancer care
inferredcites →https://doi.org/10.1038/srep46450openalex-snapshot
Accurate and reproducible invasive breast cancer detection in whole-slide images: A Deep Learning approach for quantifying tumor extent
inferredcites →https://doi.org/10.1093/wentk/9780190234775.001.0001openalex-snapshot
Genomics and Personalized Medicine
inferredcites →https://doi.org/10.1097/jto.0b013e3181c6ed9bopenalex-snapshot
Refining the Diagnosis and EGFR Status of Non-small Cell Lung Carcinoma in Biopsy and Cytologic Material, Using a Panel of Mucin Staining, TTF-1, Cytokeratin 5/6, and P63, and EGFR Mutation Analysis
inferredcites →https://doi.org/10.1101/242818openalex-snapshot
Breast Cancer Histopathological Image Classification: A Deep Learning Approach
inferredcites →https://doi.org/10.1109/cvpr.2015.7298594openalex-snapshot
Going deeper with convolutions
inferredcites →https://doi.org/10.1109/cvpr.2016.308openalex-snapshot
Rethinking the Inception Architecture for Computer Vision
inferredcites →https://doi.org/10.1109/cvpr.2016.90openalex-snapshot
Deep Residual Learning for Image Recognition
inferredcites →https://doi.org/10.1109/icpr.1994.576881openalex-snapshot
Word-level training of a handwritten word recognizer based on convolutional neural networks
inferredcites →https://doi.org/10.1109/tmi.2016.2525803openalex-snapshot
Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
inferredcites →https://doi.org/10.1109/tmi.2016.2553401openalex-snapshot
Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique
inferredcites →https://doi.org/10.1136/amiajnl-2012-001469openalex-snapshot
Cancer Digital Slide Archive: an informatics resource to support integrated in silico analysis of TCGA pathology data
inferredcites →https://doi.org/10.1146/annurev-bioeng-071516-044442openalex-snapshot
Deep Learning in Medical Image Analysis
inferredcites →https://doi.org/10.1309/ajcp08iqzaogylflopenalex-snapshot
Adenosquamous Carcinoma of the Lung
inferredcites →https://doi.org/10.1371/journal.pone.0082314openalex-snapshot
Computer-Based Image Studies on Tumor Nests Mathematical Features of Breast Cancer and Their Clinical Prognostic Value
inferredcites →https://doi.org/10.1371/journal.pone.0114885openalex-snapshot
Computational Pathology to Discriminate Benign from Malignant Intraductal Proliferations of the Breast
inferredcites →https://doi.org/10.1634/theoncologist.2008-0232openalex-snapshot
The Differential Efficacy of Pemetrexed According to NSCLC Histology: A Review of Two Phase III Studies
inferredcites →https://doi.org/10.18632/oncotarget.4391openalex-snapshot
Automated tumor analysis for molecular profiling in lung cancer
inferredcites →https://doi.org/10.2217/iim.09.9openalex-snapshot
Digital pathology image analysis: opportunities and challenges
inferredcites →https://doi.org/10.3978/j.issn.2218-6751.2014.05.01openalex-snapshot
Targeted therapy for non-small cell lung cancer: current standards and the promise of the future.
inferredcites →https://doi.org/10.4103/2153-3539.119005openalex-snapshot
OpenSlide: A vendor-neutral software foundation for digital pathology
inferredcites →https://doi.org/10.48550/arxiv.1606.05718openalex-snapshot
Deep Learning for Identifying Metastatic Breast Cancer
inferredcites →https://doi.org/10.5858/arpa.2012-0033-oaopenalex-snapshot
Validation of Interobserver Agreement in Lung Cancer Assessment: Hematoxylin-Eosin Diagnostic Reproducibility for Non–Small Cell Lung Cancer: The 2004 World Health Organization Classification and Therapeutically Relevant Subsets

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/s00418-026-02490-wopenalex-snapshot
Artificial intelligence in small tissue biopsies: diagnostic applications, histochemical integration, and methodological challenges in surgical pathology
inferred← citeshttps://doi.org/10.1007/s10462-021-10121-0openalex-snapshot
A comprehensive review of computer-aided whole-slide image analysis: from datasets to feature extraction, segmentation, classification and detection approaches
inferred← citeshttps://doi.org/10.1007/s42979-023-02115-2openalex-snapshot
Image Analysis of Nuclei Histopathology Using Deep Learning: A Review of Segmentation, Detection, and Classification
inferred← citeshttps://doi.org/10.1016/j.cmpb.2021.106464openalex-snapshot
Deep embeddings and logistic regression for rapid active learning in histopathological images
inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.107108openalex-snapshot
Non-small cell lung cancer diagnosis aid with histopathological images using Explainable Deep Learning techniques
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2023.107034openalex-snapshot
A state-of-the-art survey of artificial neural networks for Whole-slide Image analysis: From popular Convolutional Neural Networks to potential visual transformers
inferred← citeshttps://doi.org/10.1016/j.joca.2020.12.018openalex-snapshot
Deep learning enables the automation of grading histological tissue engineered cartilage images for quality control standardization
inferred← citeshttps://doi.org/10.1016/j.media.2021.102032openalex-snapshot
Fine-Tuning and training of densenet for histopathology image representation using TCGA diagnostic slides
inferred← citeshttps://doi.org/10.1016/j.neunet.2022.02.020openalex-snapshot
TSFD-Net: Tissue specific feature distillation network for nuclei segmentation and classification
inferred← citeshttps://doi.org/10.1038/s41467-023-43172-8openalex-snapshot
Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images
inferred← citeshttps://doi.org/10.1038/s41591-019-0574-4openalex-snapshot
Augmented reality microscopes for cancer histopathology
inferred← citeshttps://doi.org/10.1038/s41598-021-81506-yopenalex-snapshot
Deep learning predicts postsurgical recurrence of hepatocellular carcinoma from digital histopathologic images
inferred← citeshttps://doi.org/10.1038/s41698-025-00940-7openalex-snapshot
Systematic scoping review of external validation studies of AI pathology models for lung cancer diagnosis
inferred← citeshttps://doi.org/10.1101/2021.07.27.21261075openalex-snapshot
Small Patient Datasets Reveal Genetic Drivers of Non-Small Cell Lung Cancer Subtypes Using a Novel Machine Learning Approach
inferred← citeshttps://doi.org/10.1145/3451421.3451437openalex-snapshot
A Brief Review of Computer-aided Whole-slide Image Detection Techniques
inferred← citeshttps://doi.org/10.3390/bioengineering9090423openalex-snapshot
Development and Evaluation of a Novel Deep-Learning-Based Framework for the Classification of Renal Histopathology Images
inferred← citeshttps://doi.org/10.3390/cancers11111673openalex-snapshot
Artificial Intelligence in Lung Cancer Pathology Image Analysis
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