Epidemiology of triple-negative breast cancer: a review
FM Howard, OI Olopade - The Cancer Journal, 2021 - journals.lww.com
Triple-negative breast cancer accounted for 12% of breast cancers diagnosed in the United
States from 2012 to 2016, with a 5-year survival 8% to 16% lower than hormone receptor …
States from 2012 to 2016, with a 5-year survival 8% to 16% lower than hormone receptor …
Federated learning in medicine: facilitating multi-institutional collaborations without sharing patient data
Several studies underscore the potential of deep learning in identifying complex patterns,
leading to diagnostic and prognostic biomarkers. Identifying sufficiently large and diverse …
leading to diagnostic and prognostic biomarkers. Identifying sufficiently large and diverse …
Measuring and modelling tumour heterogeneity across scales
Cancer development, progression and therapy response are heterogeneous and patient-
specific. The biological and physical properties of tumour cells and their surrounding tissue …
specific. The biological and physical properties of tumour cells and their surrounding tissue …
Understanding and mitigating bias in imaging artificial intelligence
Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model
development, with potential for exacerbating health disparities. However, bias in imaging AI …
development, with potential for exacerbating health disparities. However, bias in imaging AI …
[HTML][HTML] QU-BraTS: MICCAI BraTS 2020 challenge on quantifying uncertainty in brain tumor segmentation-analysis of ranking scores and benchmarking results
Deep learning (DL) models have provided state-of-the-art performance in various medical
imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) …
imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) …
Breast cancer population attributable risk proportions associated with body mass index and breast density by race/ethnicity and menopausal status
Background: Overweight/obesity and dense breasts are strong breast cancer risk factors
whose prevalences vary by race/ethnicity. The breast cancer population attributable risk …
whose prevalences vary by race/ethnicity. The breast cancer population attributable risk …
[HTML][HTML] Deep-LIBRA: An artificial-intelligence method for robust quantification of breast density with independent validation in breast cancer risk assessment
Breast density is an important risk factor for breast cancer that also affects the specificity and
sensitivity of screening mammography. Current federal legislation mandates reporting of …
sensitivity of screening mammography. Current federal legislation mandates reporting of …
Impact of artificial intelligence system and volumetric density on risk prediction of interval, screen-detected, and advanced breast cancer
CM Vachon, CG Scott, AD Norman… - Journal of Clinical …, 2023 - ascopubs.org
PURPOSE Artificial intelligence (AI) algorithms improve breast cancer detection on
mammography, but their contribution to long-term risk prediction for advanced and interval …
mammography, but their contribution to long-term risk prediction for advanced and interval …
Breast cancer in dense breasts: detection challenges and supplemental screening opportunities
AL Brown, C Vijapura, M Patel, A De La Cruz… - …, 2023 - pubs.rsna.org
Dense breast tissue at mammography is associated with higher breast cancer incidence and
mortality rates, which have prompted new considerations for breast cancer screening in …
mortality rates, which have prompted new considerations for breast cancer screening in …
Postpartum involution and cancer: an opportunity for targeted breast cancer prevention and treatments?
Childbirth at any age confers a transient increased risk for breast cancer in the first decade
postpartum and this window of adverse effect extends over two decades in women with late …
postpartum and this window of adverse effect extends over two decades in women with late …