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eess.IV2023★ 11 cited
Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data
Yiqiu Shen, Jungkyu Park, Frank Yeung +4
Breast cancer screening, primarily conducted through mammography, is often supplemented with ultrasound for women with dense breast tissue. However, existing deep learning models a…
eess.IV2020★ 2 cited
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms
Nan Wu, Zhe Huang, Yiqiu Shen +8
Breast cancer is the most common cancer in women, and hundreds of thousands of unnecessary biopsies are done around the world at a tremendous cost. It is crucial to reduce the rate…
eess.IV2019
Screening Mammogram Classification with Prior Exams
Jungkyu Park, Jason Phang, Yiqiu Shen +5
Radiologists typically compare a patient's most recent breast cancer screening exam to their previous ones in making informed diagnoses. To reflect this practice, we propose new ne…