Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations

BOADICEA: a comprehensive breast cancer risk prediction model incorporating genetic and nongenetic risk factors

(2019) Andrew Lee et al.   GENETICS IN MEDICINE

Improving the diagnostic accuracy of a stratified screening strategy by identifying the optimal risk cutoff

(2019) John T. Brinton et al.   CANCER CAUSES & CONTROL

Surveillance for cancer recurrence in long-term young breast cancer survivors randomly selected from a statewide cancer registry

(2018) Tarsha Jones et al.   BREAST CANCER RESEARCH AND TREATMENT

Mammography screening: A major issue in medicine

(2018) Philippe Autier et al.   EUROPEAN JOURNAL OF CANCER

A closer look at cross-validation for assessing the accuracy of gene regulatory networks and models

(2018) Shayan Tabe-Bordbar et al.   Scientific Reports

Annual Report to the Nation on the Status of Cancer, 1975–2014, Featuring Survival

(2017) Ahmedin Jemal et al.   JNCI-Journal of the National Cancer Institute

ACR Appropriateness Criteria ® Breast Cancer Screening

(2017) Martha B. Mainiero et al.   Journal of the American College of Radiology

Annual Report to the Nation on the Status of Cancer, 1975–2014, Featuring Survival

(2017) Ahmedin Jemal et al.   JNCI-Journal of the National Cancer Institute

Genomic risk prediction of aromatase inhibitor-related arthralgia in patients with breast cancer using a novel machine-learning algorithm

(2017) Raquel E. Reinbolt et al.   Cancer Medicine

Mammography rates after the 2009 revision to the United States Preventive Services Task Force breast cancer screening recommendation

(2016) Xuanzi Qin et al.   CANCER CAUSES & CONTROL

Position paper on screening for breast cancer by the European Society of Breast Imaging (EUSOBI) and 30 national breast radiology bodies from Austria, Belgium, Bosnia and Herzegovina, Bulgaria, Croatia, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Israel, Lithuania, Moldova, The Netherlands, Norway, Poland, Portugal, Romania, Serbia, Slovakia, Spain, Sweden, Switzerland and Turkey

(2016) Francesco Sardanelli et al.   EUROPEAN RADIOLOGY

Predicting the Future — Big Data, Machine Learning, and Clinical Medicine

(2016) Ziad Obermeyer et al.   NEW ENGLAND JOURNAL OF MEDICINE

Breast Cancer Risk From Modifiable and Nonmodifiable Risk Factors Among White Women in the United States

(2016) Paige Maas et al.   JAMA Oncology

Predictive Big Data Analytics: A Study of Parkinson’s Disease Using Large, Complex, Heterogeneous, Incongruent, Multi-Source and Incomplete Observations

(2016) Ivo D. Dinov et al.   PLoS One

The Basic Facts of Korean Breast Cancer in 2012: Results from a Nationwide Survey and Breast Cancer Registry Database

(2015) Zisun Kim et al.   Journal of Breast Cancer

Breast-Cancer Screening — Viewpoint of the IARC Working Group

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

Breast Cancer in Young Women

(2015) Shoshana M. Rosenberg et al.   JAMA Oncology

Machine learning applications in cancer prognosis and prediction

(2015) Konstantina Kourou et al.   Computational and Structural Biotechnology Journal

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

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

Population-Based Screening forBRCA1andBRCA2

(2014) Mary-Claire King et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Cost-Effectiveness and Harm-Benefit Analyses of Risk-Based Screening Strategies for Breast Cancer

(2014) Ester Vilaprinyo et al.   PLoS One

Switzerland debates dismantling its breast cancer screening programme

(2014) S. Arie   BMJ-British Medical Journal

Using Clinical Factors and Mammographic Breast Density to Estimate Breast Cancer Risk: Development and Validation of a New Predictive Model

(2013) Jeffrey A. Tice et al.   ANNALS OF INTERNAL MEDICINE

Screening for Breast Cancer: An Update for the U.S. Preventive Services Task Force

(2013) Heidi D. Nelson   ANNALS OF INTERNAL MEDICINE

Effects of Mammography Screening Under Different Screening Schedules: Model Estimates of Potential Benefits and Harms

(2013) Jeanne S. Mandelblatt   ANNALS OF INTERNAL MEDICINE

Personalizing Mammography by Breast Density and Other Risk Factors for Breast Cancer: Analysis of Health Benefits and Cost-Effectiveness

(2013) John T. Schousboe et al.   ANNALS OF INTERNAL MEDICINE

Tipping the Balance of Benefits and Harms to Favor Screening Mammography Starting at Age 40 Years

(2013) Nicolien T. van Ravesteyn   ANNALS OF INTERNAL MEDICINE

The Inevitable Application of Big Data to Health Care

(2013) Travis B. Murdoch et al.   JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION

Assessment of performance of survival prediction models for cancer prognosis

(2012) Hung-Chia Chen et al.   BMC Medical Research Methodology

A systematic review of breast cancer incidence risk prediction models with meta-analysis of their performance

(2011) Catherine Meads et al.   BREAST CANCER RESEARCH AND TREATMENT

Polygenic susceptibility to prostate and breast cancer: implications for personalised screening

(2011) N Pashayan et al.   BRITISH JOURNAL OF CANCER

A comparison of machine learning techniques for survival prediction in breast cancer

(2011) Leonardo Vanneschi et al.   BioData Mining