Stand-Alone Artificial Intelligence for Breast Cancer Detection in Mammography: Comparison With 101 Radiologists

Synthetic 2-Dimensional Mammography Can Replace Digital Mammography as an Adjunct to Wide-Angle Digital Breast Tomosynthesis

(2018) Paola Clauser et al.   INVESTIGATIVE RADIOLOGY

One-view digital breast tomosynthesis as a stand-alone modality for breast cancer detection: do we need more?

(2017) Alejandro Rodriguez-Ruiz et al.   EUROPEAN RADIOLOGY

Diagnostic value of the stand-alone synthetic image in digital breast tomosynthesis examinations

(2017) Julia Garayoa et al.   EUROPEAN RADIOLOGY

Deep Learning in Mammography

(2017) Anton S. Becker et al.   INVESTIGATIVE RADIOLOGY

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

(2017) Babak Ehteshami Bejnordi et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Large scale deep learning for computer aided detection of mammographic lesions

(2017) Thijs Kooi et al.   MEDICAL IMAGE ANALYSIS

A survey on deep learning in medical image analysis

(2017) Geert Litjens et al.   MEDICAL IMAGE ANALYSIS

Will Machine Learning Tip the Balance in Breast Cancer Screening?

(2017) Andrew D. Trister et al.   JAMA Oncology

Characteristics and prognosis of interval cancers after biennial screen-film or full-field digital screening mammography

(2016) Roy J. P. Weber et al.   BREAST CANCER RESEARCH AND TREATMENT

Breast cancer screening with digital breast tomosynthesis

(2016) Per Skaane   Breast Cancer

Breast-Cancer Screening — Viewpoint of the IARC Working Group

(2015) Béatrice Lauby-Secretan et al.   NEW ENGLAND JOURNAL OF MEDICINE

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

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

The average receiver operating characteristic curve in multireader multicase imaging studies

(2014) W Chen et al.   BRITISH JOURNAL OF RADIOLOGY

Cancer incidence and mortality worldwide: Sources, methods and major patterns in GLOBOCAN 2012

(2014) Jacques Ferlay et al.   INTERNATIONAL JOURNAL OF CANCER

The benefits and harms of breast cancer screening: an independent review

(2013) M G Marmot et al.   BRITISH JOURNAL OF CANCER

Learning from unbalanced data: A cascade-based approach for detecting clustered microcalcifications

(2013) A. Bria et al.   MEDICAL IMAGE ANALYSIS

If You Don’t Find It Often, You Often Don’t Find It: Why Some Cancers Are Missed in Breast Cancer Screening

(2013) Karla K. Evans et al.   PLoS One

Hypothesis Testing in Noninferiority and Equivalence MRMC ROC Studies

(2012) Weijie Chen et al.   ACADEMIC RADIOLOGY

Performance comparison of single-view digital breast tomosynthesis plus single-view digital mammography with two-view digital mammography

(2012) Gisella Gennaro et al.   EUROPEAN RADIOLOGY

The Impact of Mammographic Screening on Breast Cancer Mortality in Europe: A Review of Observational Studies

(2012) Mireille Broeders et al.   JOURNAL OF MEDICAL SCREENING

Two-View and Single-View Tomosynthesis versus Full-Field Digital Mammography: High-Resolution X-Ray Imaging Observer Study

(2012) Matthew G. Wallis et al.   RADIOLOGY

Computer-aided Detection of Masses at Mammography: Interactive Decision Support versus Prompts

(2012) Rianne Hupse et al.   RADIOLOGY

Increase in perceived case suspiciousness due to local contrast optimisation in digital screening mammography

(2011) Roelant Visser et al.   EUROPEAN RADIOLOGY

BI-RADS Data Should Not Be Used to Estimate ROC Curves

(2010) Yulei Jiang et al.   RADIOLOGY

Workforce Shortages in Breast Imaging: Impact on Mammography Utilization

(2009) Paul Wing et al.   AMERICAN JOURNAL OF ROENTGENOLOGY

A Framework for Random-Effects ROC Analysis: Biases with the Bootstrap and Other Variance Estimators

(2009) Brandon D. Gallas et al.   COMMUNICATIONS IN STATISTICS-THEORY AND METHODS

Use of Normal Tissue Context in Computer-Aided Detection of Masses in Mammograms

(2009) R. Hupse et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

Single Reading with Computer-Aided Detection for Screening Mammography

(2008) Fiona J. Gilbert et al.   NEW ENGLAND JOURNAL OF MEDICINE

The “Laboratory” Effect: Comparing Radiologists' Performance and Variability during Prospective Clinical and Laboratory Mammography Interpretations

(2008) David Gur et al.   RADIOLOGY

Reader studies for validation of CAD systems

(2007) Brandon D. Gallas et al.   NEURAL NETWORKS