16 citations · 30 across the 4 of their papers we have counts for
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eess.IV2020★ 16 cited
Synthesizing lesions using contextual GANs improves breast cancer classification on mammograms
Eric Wu, Kevin Wu, William Lotter
Data scarcity and class imbalance are two fundamental challenges in many machine learning applications to healthcare. Breast cancer classification in mammography exemplifies these…
eess.IV2019★ 2 cited
Robust breast cancer detection in mammography and digital breast tomosynthesis using annotation-efficient deep learning approach
William Lotter, Abdul Rahman Diab, Bryan Haslam +10
Breast cancer remains a global challenge, causing over 1 million deaths globally in 2018. To achieve earlier breast cancer detection, screening x-ray mammography is recommended by…
eess.IV2019★ 6 cited
Validation of a deep learning mammography model in a population with low screening rates
Kevin Wu, Eric Wu, Yaping Wu +4
A key promise of AI applications in healthcare is in increasing access to quality medical care in under-served populations and emerging markets. However, deep learning models are o…