Area of research
Oncology · Artificial Intelligence
Research interest
Research interests include Mammography, Breast cancer, Medicine, Breast cancer screening, Pandemic, and Digital mammography.
Collaborative Modeling to Compare Different Breast Cancer Screening Strategies
Breast Cancer Screening Using Mammography, Digital Breast Tomosynthesis, and Magnetic Resonance Imaging by Breast Density
Establishing a Validation Infrastructure for Imaging-Based Artificial Intelligence Algorithms Before Clinical Implementation
Performance of Supplemental US Screening in Women with Dense Breasts and Varying Breast Cancer Risk: Results from the Breast Cancer Surveillance Consortium
Artificial Intelligence-Driven Mammography-Based Future Breast Cancer Risk Prediction: A Systematic Review
Digital Breast Tomosynthesis versus Digital Mammography Screening Performance on Successive Screening Rounds from the Breast Cancer Surveillance Consortium
Breast Cancer Screening Strategies for Women With <i>ATM, CHEK2</i>, and <i>PALB2</i> Pathogenic Variants
Independent External Validation of Artificial Intelligence Algorithms for Automated Interpretation of Screening Mammography: A Systematic Review
Impact of the COVID-19 Pandemic on Breast Cancer Mortality in the US: Estimates From Collaborative Simulation Modeling
Changes in Mammography Use by Women’s Characteristics During the First 5 Months of the COVID-19 Pandemic
Digital Mammography and Breast Tomosynthesis Performance in Women with a Personal History of Breast Cancer, 2007–2016
Screening Performance of Digital Breast Tomosynthesis vs Digital Mammography in Community Practice by Patient Age, Screening Round, and Breast Density
The Coronavirus Disease 2019 (COVID-19) Pandemic: A Patient-Centered Model of Systemic Shock and Cancer Care Adherence
Long-Term Outcomes and Cost-Effectiveness of Breast Cancer Screening With Digital Breast Tomosynthesis in the United States