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Hiba Chougrad et al.
NEUROCOMPUTING (2020)
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Xin Shu et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2020)
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Carlos Beltran-Perez et al.
INTERNATIONAL JOURNAL OF AUTOMATION AND COMPUTING (2020)
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Ravi K. Samala et al.
PHYSICS IN MEDICINE AND BIOLOGY (2020)
The efficacy of using computer-aided detection (CAD) for detection of breast cancer in mammography screening: a systematic review
Emilie L. Henriksen et al.
ACTA RADIOLOGICA (2019)
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Jared A. Dunnmon et al.
RADIOLOGY (2019)
Convolutional neural network improvement for breast cancer classification
Fung Fung Ting et al.
EXPERT SYSTEMS WITH APPLICATIONS (2019)
Deep Learning for Breast Cancer Diagnosis from Mammograms-A Comparative Study
Lazaros Tsochatzidis et al.
JOURNAL OF IMAGING (2019)
Simultaneous detection and classification of breast masses in digital mammograms via a deep learning YOLO-based CAD system
Mohammed A. Al-masni et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2018)
Deep Convolutional Neural Networks for breast cancer screening
Hiba Chougrad et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2018)
Deep learning in mammography and breast histology, an overview and future trends
Azam Hamidinekoo et al.
MEDICAL IMAGE ANALYSIS (2018)
Detecting and classifying lesions in mammograms with Deep Learning
Dezso Ribli et al.
SCIENTIFIC REPORTS (2018)
Large scale deep learning for computer aided detection of mammographic lesions
Thijs Kooi et al.
MEDICAL IMAGE ANALYSIS (2017)
Dermatologist-level classification of skin cancer with deep neural networks
Andre Esteva et al.
NATURE (2017)
A curated mammography data set for use in computer-aided detection and diagnosis research
Rebecca Sawyer Lee et al.
SCIENTIFIC DATA (2017)
Representation learning for mammography mass lesion classification with convolutional neural networks
John Arevalo et al.
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE (2016)
Classifier ensemble generation and selection with multiple feature representations for classification applications in computer-aided detection and diagnosis on mammography
Jae Young Choi et al.
EXPERT SYSTEMS WITH APPLICATIONS (2016)
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
Hoo-Chang Shin et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2016)
Development and Validation of a Deep Learning Algorithm for Detection of Diabetic Retinopathy in Retinal Fundus Photographs
Varun Gulshan et al.
JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION (2016)
Breast Cancer Screening An Evidence-Based Update
Mackenzie S. Fuller et al.
MEDICAL CLINICS OF NORTH AMERICA (2015)
Computer-aided classification of breast masses in mammogram images based on spherical wavelet transform and support vector machines
Pelin Gorgel et al.
EXPERT SYSTEMS (2015)
Use of volumetric features for temporal comparison of mass lesions in full field digital mammograms
Jelena Bozek et al.
MEDICAL PHYSICS (2014)
Automated Diagnosis of Mammogram Images of Breast Cancer Using Discrete Wavelet Transform and Spherical Wavelet Transform Features: A Comparative Study
Karthikeyan Ganesan et al.
TECHNOLOGY IN CANCER RESEARCH & TREATMENT (2014)
A multitarget training method for artificial neural network with application to computer-aided diagnosis
Bei Liu et al.
MEDICAL PHYSICS (2013)
Efficient Additive Kernels via Explicit Feature Maps
Andrea Vedaldi et al.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE (2012)
Breast Image Feature Learning with Adaptive Deconvolutional Networks
Andrew R. Jamieson et al.
MEDICAL IMAGING 2012: COMPUTER-AIDED DIAGNOSIS (2012)
Regularization Paths for Generalized Linear Models via Coordinate Descent
Jerome Friedman et al.
JOURNAL OF STATISTICAL SOFTWARE (2010)
A review of automatic mass detection and segmentation in mammographic images
Arnau Oliver et al.
MEDICAL IMAGE ANALYSIS (2010)
Genome-wide association study identifies eight loci associated with blood pressure
Christopher Newton-Cheh et al.
NATURE GENETICS (2009)
Temporal change analysis for characterization of mass lesions in mammography
Sheila Timp et al.
IEEE TRANSACTIONS ON MEDICAL IMAGING (2007)
Tests of equivalence and non-inferiority for diagnostic accuracy based on the paired areas under ROC curves
JP Liu et al.
STATISTICS IN MEDICINE (2006)
Effect of screening and adjuvant therapy on mortality from breast cancer
DA Berry et al.
NEW ENGLAND JOURNAL OF MEDICINE (2005)
Improvement of mammographic mass characterization using spiculation measures and morphological features
B Sahiner et al.
MEDICAL PHYSICS (2001)
Boundary modelling and shape analysis methods for classification of mammographic masses
RM Rangayyan et al.
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING (2000)
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