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Chromatin organisation and cancer prognosis: a pan-cancer study

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Deep learning based tissue analysis predicts outcome in colorectal cancer

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Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer

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Robust detection and segmentation of cell nuclei in biomedical images based on a computational topology framework

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Dermatologist-level classification of skin cancer with deep neural networks

(2017) Andre Esteva et al.   NATURE

QuPath: Open source software for digital pathology image analysis

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Immune and Stromal Classification of Colorectal Cancer Is Associated with Molecular Subtypes and Relevant for Precision Immunotherapy

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Development and Validation of a Radiomics Nomogram for Preoperative Prediction of Lymph Node Metastasis in Colorectal Cancer

(2016) Yan-qi Huang et al.   JOURNAL OF CLINICAL ONCOLOGY

Mastering the game of Go with deep neural networks and tree search

(2016) David Silver et al.   NATURE

Multi-class texture analysis in colorectal cancer histology

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Comparing computer-generated and pathologist-generated tumour segmentations for immunohistochemical scoring of breast tissue microarrays

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Transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD): The TRIPOD statement

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Statin Use and Survival After Colorectal Cancer: The Importance of Comprehensive Confounder Adjustment

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Stromal contribution to the colorectal cancer transcriptome

(2015) Claudio Isella et al.   NATURE GENETICS

The consensus molecular subtypes of colorectal cancer

(2015) Justin Guinney et al.   NATURE MEDICINE

Continuous representation of tumor microvessel density and detection of angiogenic hotspots in histological whole-slide images

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Statin Use and Survival After Colorectal Cancer: The Importance of Comprehensive Confounder Adjustment

(2015) Michael Hoffmeister et al.   JNCI-Journal of the National Cancer Institute

Decoding tumour phenotype by noninvasive imaging using a quantitative radiomics approach

(2014) Hugo J. W. L. Aerts et al.   Nature Communications

Automatic Nuclei Segmentation in H&E Stained Breast Cancer Histopathology Images

(2013) Mitko Veta et al.   PLoS One

Deep Neural Networks for Acoustic Modeling in Speech Recognition: The Shared Views of Four Research Groups

(2012) Geoffrey Hinton et al.   IEEE SIGNAL PROCESSING MAGAZINE

Promise and pitfalls of quantitative imaging in oncology clinical trials

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Comprehensive molecular characterization of human colon and rectal cancer

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Absolute quantification of somatic DNA alterations in human cancer

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Multi-column deep neural network for traffic sign classification

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Quantitative Image Analysis of Cellular Heterogeneity in Breast Tumors Complements Genomic Profiling

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Localization and Density of Immune Cells in the Invasive Margin of Human Colorectal Cancer Liver Metastases Are Prognostic for Response to Chemotherapy

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Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition

(2011) G. E. Dahl et al.   IEEE Transactions on Audio Speech and Language Processing

Long-Term Risk of Colorectal Cancer After Negative Colonoscopy

(2011) Hermann Brenner et al.   JOURNAL OF CLINICAL ONCOLOGY

Clinical Applications of Metabolomics in Oncology: A Review

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Quantitative imaging biomarkers in neuro-oncology

(2009) Adam D. Waldman et al.   Nature Reviews Clinical Oncology

Quantitative imaging biomarkers in the clinical development of targeted therapeutics: current and future perspectives

(2008) James PB O'Connor et al.   LANCET ONCOLOGY