Performance comparison of deep learning and segmentation-based radiomic methods in the task of distinguishing benign and malignant breast lesions on DCE-MRI. - Natasha Antropova; Benjamin Q. Huynh; Maryellen L. Giger (Computer-Aided Diagnosis, 2017)

Deep learning and three-compartment breast imaging in breast cancer diagnosis. - Karen Drukker; Benjamin Q. Huynh; Maryellen L. Giger; Serghei Malkov; Jesús I. Ávila; Bo Fan 001; Bonnie N. Joe; Karla Kerlikowske; Jennifer S. Drukteinis; Leila Kazemi; Malesa M. Pereira; John Shepherd 002 (Computer-Aided Diagnosis, 2017)

Comparison of breast DCE-MRI contrast time points for predicting response to neoadjuvant chemotherapy using deep convolutional neural network features with transfer learning. - Benjamin Q. Huynh; Natasha Antropova; Maryellen L. Giger (Computer-Aided Diagnosis, 2017)

Recurrent neural networks for breast lesion classification based on DCE-MRIs. - Natasha Antropova; Benjamin Q. Huynh; Maryellen L. Giger (Computer-Aided Diagnosis, 2018)

Potential for allocative harm in an environmental justice data tool. - Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf (CoRR, 2023)

AI for Anticipatory Action: Moving Beyond Climate Forecasting. - Benjamin Q. Huynh; Mathew V. Kiang (CoRR, 2023)

Mitigating allocative tradeoffs and harms in an environmental justice data tool. - Benjamin Q. Huynh; Elizabeth T. Chin; Allison Koenecke; Derek Ouyang; Daniel E. Ho; Mathew V. Kiang; David H. Rehkopf (Nat. Mac. Intell., 2024)