Deep learning in breast cancer risk assessment: evaluation of fine-tuned convolutional neural networks on a clinical dataset of FFDMs

2018 ◽  
Author(s):  
Hui Li ◽  
Maryellen L. Giger ◽  
Kayla R. Mendel ◽  
John Lee ◽  
Li Lan
Keyword(s):  
Breast Cancer ◽  
Neural Networks ◽  
Risk Assessment ◽  
Deep Learning ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Convolutional Neural Networks ◽  
Cancer Risk Assessment ◽  
Clinical Dataset ◽  
Breast Cancer Risk Assessment

scholarly journals Breast Cancer Risk Assessment: A Review on Mammography-Based Approaches

2021 ◽  
Vol 7 (6) ◽  
pp. 98
Author(s):  
João Mendes ◽  
Nuno Matela
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Deep Learning ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Machine Learning Algorithms ◽  
Cancer Risk Assessment ◽  
Cancer Statistics ◽  
Screening Programs ◽  
Breast Cancer Risk Assessment

Breast cancer affects thousands of women across the world, every year. Methods to predict risk of breast cancer, or to stratify women in different risk levels, could help to achieve an early diagnosis, and consequently a reduction of mortality. This paper aims to review articles that extracted texture features from mammograms and used those features along with machine learning algorithms to assess breast cancer risk. Besides that, deep learning methodologies that aimed for the same goal were also reviewed. In this work, first, a brief introduction to breast cancer statistics and screening programs is presented; after that, research done in the field of breast cancer risk assessment are analyzed, in terms of both methodologies used and results obtained. Finally, considerations about the analyzed papers are conducted. The results of this review allow to conclude that both machine and deep learning methodologies provide promising results in the field of risk analysis, either in a stratification in risk groups, or in a prediction of a risk score. Although promising, future endeavors in this field should consider the possibility of the implementation of the methodology in clinical practice.

scholarly journals SNPs for breast cancer risk assessment

Oncotarget ◽  
2017 ◽  
Vol 8 (59) ◽  
pp. 99211-99212 ◽  
Author(s):  
Jack Cuzick ◽  
Adam Brentnall ◽  
Mitchell Dowsett
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Risk Assessment ◽  
Breast Cancer Risk Assessment

scholarly journals Bayesian joint ordinal and survival modeling for breast cancer risk assessment

2016 ◽  
Vol 35 (28) ◽  
pp. 5267-5282 ◽  
Author(s):  
C. Armero ◽  
C. Forné ◽  
M. Rué ◽  
A. Forte ◽  
H. Perpiñán ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Risk Assessment ◽  
Breast Cancer Risk Assessment ◽  
Survival Modeling

scholarly journals Commentary ACOG Practice Bulletin July 2017: Breast Cancer Risk Assessment and Screening in Average-Risk Women

2018 ◽  
Vol 91 (1090) ◽  
pp. 20170907 ◽  
Author(s):  
Victoria Mango ◽  
Yolanda Bryce ◽  
Elizabeth Anne Morris ◽  
Elisabetta Gianotti ◽  
Katja Pinker
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Risk Assessment ◽  
Average Risk ◽  
Breast Cancer Risk Assessment

scholarly journals The iPrevent Online Breast Cancer Risk Assessment and Risk Management Tool: Usability and Acceptability Testing

2018 ◽  
Vol 2 (2) ◽  
pp. e24 ◽  
Author(s):  
Louisa L Lo ◽  
Ian M Collins ◽  
Mathias Bressel ◽  
Phyllis Butow ◽  
Jon Emery ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Risk Assessment ◽  
Risk Management ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Cancer Risk Assessment ◽  
Management Tool ◽  
Breast Cancer Risk Assessment
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