Publications

(2021). Lessons from the first DBTex Challenge. Nature Machine Intelligence.

PDF

(2021). Artificial Intelligence System Reduces False-Positive Findings in the Interpretation of Breast Ultrasound Exams.

PDF

(2020). Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability.

PDF

(2020). Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms.

PDF

(2020). An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.

PDF Code

(2020). Improving the Ability of Deep Neural Networks to Use Information From Multiple Views in Breast Cancer Screening. Proceedings of Machine Learning Research.

PDF

(2020). An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.

PDF Code

(2019). Globally-Aware Multiple Instance Classifier for Breast Cancer Screening. MIML 2019.

PDF

(2019). Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. IEEE Transactions on Medical Imaging.

PDF Code

(2019). Screening Mammogram Classification with Prior Exams. MIDL 2019.

PDF

(2018). The Evolution of Shared Concepts in Changing Populations. Review of Philosophy and Psychology.

DOI