Toward robust mammography-based models for breast cancer risk

International evaluation of an AI system for breast cancer screening

(2020) Scott Mayer McKinney et al.   NATURE

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization

(2020) Yiqiu Shen et al.   MEDICAL IMAGE ANALYSIS

Cancer screening in the United States, 2019: A review of current American Cancer Society guidelines and current issues in cancer screening

(2019) Robert A. Smith et al.   CA-A CANCER JOURNAL FOR CLINICIANS

End-to-end lung cancer screening with three-dimensional deep learning on low-dose chest computed tomography

(2019) Diego Ardila et al.   NATURE MEDICINE

A Deep Learning Mammography-based Model for Improved Breast Cancer Risk Prediction

(2019) Adam Yala et al.   RADIOLOGY

Medication Use to Reduce Risk of Breast Cancer

(2019) et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Predicting Breast Cancer by Applying Deep Learning to Linked Health Records and Mammograms

(2019) Ayelet Akselrod-Ballin et al.   RADIOLOGY

Deep learning-based classification of mesothelioma improves prediction of patient outcome

(2019) Pierre Courtiol et al.   NATURE MEDICINE

Supplemental MRI Screening for Women with Extremely Dense Breast Tissue

(2019) Marije F. Bakker et al.   NEW ENGLAND JOURNAL OF MEDICINE

A Deep Learning Model to Triage Screening Mammograms: A Simulation Study

(2019) Adam Yala et al.   RADIOLOGY

Deep Learning to Improve Breast Cancer Detection on Screening Mammography

(2019) Li Shen et al.   Scientific Reports

A Multi-million Mammography Image Dataset and Population-Based Screening Cohort for the Training and Evaluation of Deep Neural Networks—the Cohort of Screen-Aged Women (CSAW)

(2019) Karin Dembrower et al.   JOURNAL OF DIGITAL IMAGING

Comparison of a Deep Learning Risk Score and Standard Mammographic Density Score for Breast Cancer Risk Prediction

(2019) Karin Dembrower et al.   RADIOLOGY

Deep Neural Networks Improve Radiologists’ Performance in Breast Cancer Screening

(2019) Nan Wu et al.   IEEE TRANSACTIONS ON MEDICAL IMAGING

DeepSurv: personalized treatment recommender system using a Cox proportional hazards deep neural network

(2018) Jared L. Katzman et al.   BMC Medical Research Methodology

Detecting and classifying lesions in mammograms with Deep Learning

(2018) Dezső Ribli et al.   Scientific Reports

Breast Cancer Screening in Women at Higher-Than-Average Risk: Recommendations From the ACR

(2018) Debra L. Monticciolo et al.   Journal of the American College of Radiology

Prediction of cardiovascular risk factors from retinal fundus photographs via deep learning

(2018) Ryan Poplin et al.   Nature Biomedical Engineering

Cardiologist-level arrhythmia detection and classification in ambulatory electrocardiograms using a deep neural network

(2018) Awni Y. Hannun et al.   NATURE MEDICINE

Mammographic Breast Density Assessment Using Deep Learning: Clinical Implementation

(2018) Constance D. Lehman et al.   RADIOLOGY

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

(2018) Alejandro Rodriguez-Ruiz et al.   JNCI-Journal of the National Cancer Institute

Breast Cancer Screening for Average-Risk Women: Recommendations From the ACR Commission on Breast Imaging

(2017) Debra L. Monticciolo et al.   Journal of the American College of Radiology

A Deep Learning-Based Radiomics Model for Prediction of Survival in Glioblastoma Multiforme

(2017) Jiangwei Lao et al.   Scientific Reports

Screening for Breast Cancer: U.S. Preventive Services Task Force Recommendation Statement

(2016) Albert L. Siu et al.   ANNALS OF INTERNAL MEDICINE

Screening for Cancer: Advice for High-Value Care From the American College of Physicians

(2015) Timothy J. Wilt et al.   ANNALS OF INTERNAL MEDICINE

ImageNet Large Scale Visual Recognition Challenge

(2015) Olga Russakovsky et al.   INTERNATIONAL JOURNAL OF COMPUTER VISION

Breast Cancer Screening for Women at Average Risk

(2015) Kevin C. Oeffinger et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Breast Cancer Risk Reduction, Version 2.2015

(2015) Therese B. Bevers et al.   Journal of the National Comprehensive Cancer Network

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

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

Insights from the Breast Cancer Screening Trials: How Screening Affects the Natural History of Breast Cancer and Implications for Evaluating Service Screening Programs

(2014) László Tabár et al.   Breast Journal

Systematic review and meta-analysis of the current evidence on the duration of protection by bacillus Calmette–Guérin vaccination against tuberculosis

(2014) I Abubakar et al.   HEALTH TECHNOLOGY ASSESSMENT

Pan-Canadian Study of Mammography Screening and Mortality from Breast Cancer

(2014) Andrew Coldman et al.   JNCI-Journal of the National Cancer Institute

Consequences of False-Positive Screening Mammograms

(2014) Anna N. A. Tosteson et al.   JAMA Internal Medicine

Long-Term Psychosocial Consequences of False-Positive Screening Mammography

(2013) J. Brodersen et al.   ANNALS OF FAMILY MEDICINE

Cost-Effectiveness of Digital Mammography Breast Cancer Screening

(2013) Anna N.A. Tosteson et al.   ANNALS OF INTERNAL MEDICINE

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

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

Use of Pharmacologic Interventions for Breast Cancer Risk Reduction: American Society of Clinical Oncology Clinical Practice Guideline

(2013) Kala Visvanathan et al.   JOURNAL OF CLINICAL ONCOLOGY

The Cost of Breast Cancer Screening in the Medicare Population

(2013) Cary P. Gross et al.   JAMA Internal Medicine

The Benefits and Harms of Mammographic Screening for Breast Cancer: Building the Evidence Base Using Service Screening Programmes

(2012) Allan Hackshaw   JOURNAL OF MEDICAL SCREENING

Multiobjective evolutionary algorithms to identify highly autocorrelated areas: the case of spatial distribution in financially compromised farms

(2011) Carlos R. García-Alonso et al.   ANNALS OF OPERATIONS RESEARCH

pROC: an open-source package for R and S+ to analyze and compare ROC curves

(2011) Xavier Robin et al.   BMC BIOINFORMATICS

On the C-statistics for evaluating overall adequacy of risk prediction procedures with censored survival data

(2011) Hajime Uno et al.   STATISTICS IN MEDICINE

NWChem: A comprehensive and scalable open-source solution for large scale molecular simulations

(2010) M. Valiev et al.   COMPUTER PHYSICS COMMUNICATIONS

Meta-analyses of the effect of false-positive mammograms on generic and specific psychosocial outcomes

(2010) Talya Salz et al.   PSYCHO-ONCOLOGY