Patient Graph Deep Learning to Predict Breast Cancer Molecular Subtype

Genenames.org: the HGNC resources in 2023

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Deep Learning for Automated Triaging of 4581 Breast MRI Examinations from the DENSE Trial

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The Impact of Normalization Approaches to Automatically Detect Radiogenomic Phenotypes Characterizing Breast Cancer Receptors Status

(2020) Rossana Castaldo et al.   Cancers

A harmonized meta-knowledgebase of clinical interpretations of somatic genomic variants in cancer

(2020) Alex H. Wagner et al.   NATURE GENETICS

Early Prediction of Response to Neoadjuvant Chemotherapy in Breast Cancer Sonography Using Siamese Convolutional Neural Networks

(2020) Michal Byra et al.   IEEE Journal of Biomedical and Health Informatics

Investigating Deep Learning Based Breast Cancer Subtyping Using Pan-Cancer and Multi-Omic Data

(2020) Francisco Cristovao et al.   IEEE-ACM Transactions on Computational Biology and Bioinformatics

Artificial intelligence in cancer imaging: Clinical challenges and applications

(2019) Wenya Linda Bi et al.   CA-A CANCER JOURNAL FOR CLINICIANS

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(2019) A. C. Picornell et al.   BMC GENOMICS

Joint Prediction of Breast Cancer Histological Grade and Ki-67 Expression Level Based on DCE-MRI and DWI Radiomics

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A multimodal deep neural network for human breast cancer prognosis prediction by integrating multi-dimensional data

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Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment

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Utilization of Computer-Aided Detection for Digital Screening Mammography in the United States, 2008 to 2016

(2018) John D. Keen et al.   Journal of the American College of Radiology

OUP accepted manuscript

(2018)   JOURNAL OF RADIATION RESEARCH

Quantitative imaging of cancer in the postgenomic era: Radio(geno)mics, deep learning, and habitats

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Identifying relations between imaging phenotypes and molecular subtypes of breast cancer: Model discovery and external validation

(2017) Jia Wu et al.   JOURNAL OF MAGNETIC RESONANCE IMAGING

Precision medicine in breast cancer: reality or utopia?

(2017) Ali Bettaieb et al.   Journal of Translational Medicine

A deep feature fusion methodology for breast cancer diagnosis demonstrated on three imaging modality datasets

(2017) Natalia Antropova et al.   MEDICAL PHYSICS

AACR Project GENIE: Powering Precision Medicine through an International Consortium

(2017)   Cancer Discovery

$\mathtt {Deepr}$: A Convolutional Net for Medical Records

(2017) Phuoc Nguyen et al.   IEEE Journal of Biomedical and Health Informatics

Toward a Shared Vision for Cancer Genomic Data

(2016) Robert L. Grossman et al.   NEW ENGLAND JOURNAL OF MEDICINE

Computational approach to radiogenomics of breast cancer: Luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using computer vision algorithms

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Memorial Sloan Kettering-Integrated Mutation Profiling of Actionable Cancer Targets (MSK-IMPACT)

(2015) Donavan T. Cheng et al.   JOURNAL OF MOLECULAR DIAGNOSTICS

Precision Medicine in Breast Cancer: Genes, Genomes, and the Future of Genomically Driven Treatments

(2015) Daniel G. Stover et al.   Current Oncology Reports

Diagnostic Accuracy of Digital Screening Mammography With and Without Computer-Aided Detection

(2015) Constance D. Lehman et al.   JAMA Internal Medicine

The Precision-Recall Plot Is More Informative than the ROC Plot When Evaluating Binary Classifiers on Imbalanced Datasets

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Impact of Computer-Aided Detection Systems on Radiologist Accuracy With Digital Mammography

(2014) Elodia B. Cole et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

Implementing personalized cancer care

(2014) Richard L. Schilsky   Nature Reviews Clinical Oncology

Radiogenomic Analysis of Breast Cancer: Luminal B Molecular Subtype Is Associated with Enhancement Dynamics at MR Imaging

(2014) Maciej A. Mazurowski et al.   RADIOLOGY

Molecular and Cellular Heterogeneity in Breast Cancer

(2013) Ashley G. Rivenbark et al.   AMERICAN JOURNAL OF PATHOLOGY

Short-Term Outcomes of Screening Mammography Using Computer-Aided Detection

(2013) Joshua J. Fenton et al.   ANNALS OF INTERNAL MEDICINE

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Radiogenomic Analysis of Breast Cancer Using MRI: A Preliminary Study to Define the Landscape

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(2012) Daniel C. Koboldt et al.   NATURE

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