Standalone AI for breast cancer detection at screening digital mammography and digital breast tomosynthesis: a systematic review and meta-analysis
Background There is considerable interest in the potential use of artificial intelligence (AI)
systems in mammographic screening. However, it is essential to critically evaluate the …
systems in mammographic screening. However, it is essential to critically evaluate the …
Artificial intelligence applications in breast imaging: current status and future directions
CR Taylor, N Monga, C Johnson, JR Hawley, M Patel - Diagnostics, 2023 - mdpi.com
Attempts to use computers to aid in the detection of breast malignancies date back more
than 20 years. Despite significant interest and investment, this has historically led to minimal …
than 20 years. Despite significant interest and investment, this has historically led to minimal …
Interval cancer detection using a neural network and breast density in women with negative screening mammograms
AJT Wanders, W Mees, PAM Bun, N Janssen… - Radiology, 2022 - pubs.rsna.org
Background Inclusion of mammographic breast density (BD) in breast cancer risk models
improves accuracy, but accuracy remains modest. Interval cancer (IC) risk prediction may be …
improves accuracy, but accuracy remains modest. Interval cancer (IC) risk prediction may be …
Deep learning in breast cancer imaging: A decade of progress and future directions
Breast cancer has reached the highest incidence rate worldwide among all malignancies
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
since 2020. Breast imaging plays a significant role in early diagnosis and intervention to …
Deep learning in breast imaging
A Bhowmik, S Eskreis-Winkler - BJR| Open, 2022 - academic.oup.com
Millions of breast imaging exams are performed each year in an effort to reduce the
morbidity and mortality of breast cancer. Breast imaging exams are performed for cancer …
morbidity and mortality of breast cancer. Breast imaging exams are performed for cancer …
The role of deep learning in advancing breast cancer detection using different imaging modalities: a systematic review
Simple Summary Breast cancer is the most common cancer, which resulted in the death of
700,000 people around the world in 2020. Various imaging modalities have been utilized to …
700,000 people around the world in 2020. Various imaging modalities have been utilized to …
Breast cancer risk prediction combining a convolutional neural network-based mammographic evaluation with clinical factors
Purpose Deep learning techniques, including convolutional neural networks (CNN), have
the potential to improve breast cancer risk prediction compared to traditional risk models. We …
the potential to improve breast cancer risk prediction compared to traditional risk models. We …
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 screening with digital breast tomosynthesis: comparison of different reading strategies implementing artificial intelligence
V Dahlblom, M Dustler, A Tingberg, S Zackrisson - European Radiology, 2023 - Springer
Objectives Digital breast tomosynthesis (DBT) can detect more cancers than the current
standard breast screening method, digital mammography (DM); however, it can substantially …
standard breast screening method, digital mammography (DM); however, it can substantially …
Early indicators of the impact of using AI in mammography screening for breast cancer
Background Retrospective studies have suggested that using artificial intelligence (AI) may
decrease the workload of radiologists while preserving mammography screening …
decrease the workload of radiologists while preserving mammography screening …