Understanding the robustness of deep neural network classifiers for breast cancer screening. - Witold Oleszkiewicz; Taro Makino; Stanislaw Jastrzebski; Tomasz Trzcinski; Linda Moy; Kyunghyun Cho; Laura Heacock; Krzysztof J. Geras (CoRR, 2020)

Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms. - Nan Wu; Zhe Huang 005; Yiqiu Shen; Jungkyu Park 001; Jason Phang; Taro Makino; Sungheon Gene Kim; Kyunghyun Cho; Laura Heacock; Linda Moy; Krzysztof J. Geras (CoRR, 2020)

Differences between human and machine perception in medical diagnosis. - Taro Makino; Stanislaw Jastrzebski; Witold Oleszkiewicz; Celin Chacko; Robin Ehrenpreis; Naziya Samreen; Chloe Chhor; Eric Kim; Jiyon Lee; Kristine Pysarenko; Beatriu Reig; Hildegard Toth; et al. (CoRR, 2020)

Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening. - Nan Wu; Jason Phang; Jungkyu Park 001; Yiqiu Shen; Zhe Huang 005; Masha Zorin; Stanislaw Jastrzebski; Thibault Févry; Joe Katsnelson; Eric Kim; Stacey Wolfson; Ujas Parikh; et al. (IEEE Trans. Medical Imaging, 2020)

A Simulation Pipeline to Generate Realistic Breast Images for Learning DCE-MRI Reconstruction. - Zhengnan Huang; Jonghyun Bae; Patricia M. Johnson; Terlika Sood; Laura Heacock; Justin Fogarty; Linda Moy; Sungheon Gene Kim; Florian Knoll (MLMIR@MICCAI, 2021)

Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms. - Nan Wu; Zhe Huang 005; Yiqiu Shen; Jungkyu Park 001; Jason Phang; Taro Makino; Sungheon Gene Kim; Kyunghyun Cho; Laura Heacock; Linda Moy; Krzysztof J. Geras (J. Digit. Imaging, 2021)

An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization. - Yiqiu Shen; Nan Wu; Jason Phang; Jungkyu Park 001; Kangning Liu; Sudarshini Tyagi; Laura Heacock; Sungheon Gene Kim; Linda Moy; Kyunghyun Cho; Krzysztof J. Geras (Medical Image Anal., 2021)

Lessons from the first DBTex Challenge. - Jungkyu Park 001; Yoel Shoshan; Robert Martí; Pablo Gómez del Campo; Vadim Ratner; Daniel Khapun; Aviad Zlotnick; Ella Barkan; Flora Gilboa-Solomon; Jakub Chledowski; Jan Witowski; Alexandra Millet; et al. (Nat. Mach. Intell., 2021)

3D-GMIC: an efficient deep neural network to find small objects in large 3D images. - Jungkyu Park 001; Jakub Chledowski; Stanislaw Jastrzebski; Jan Witowski; Yanqi Xu; Linda Du; Sushma Gaddam; Eric Kim; Alana Lewin; Ujas Parikh; Anastasia Plaunova; Sardius Chen; et al. (CoRR, 2022)

BenchMD: A Benchmark for Modality-Agnostic Learning on Medical Images and Sensors. - Kathryn Wantlin; Chenwei Wu 006; Shih-Cheng Huang; Oishi Banerjee; Farah Dadabhoy; Veeral Vipin Mehta; Ryan Wonhee Han; Fang Cao; Raja R. Narayan; Errol Colak; Adewole S. Adamson; Laura Heacock; et al. (CoRR, 2023)

Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data. - Yiqiu Shen; Jungkyu Park 001; Frank Yeung; Eliana Goldberg; Laura Heacock; Farah Shamout; Krzysztof J. Geras (CoRR, 2023)

Understanding differences in applying DETR to natural and medical images. - Yanqi Xu; Yiqiu Shen; Carlos Fernandez-Granda; Laura Heacock; Krzysztof J. Geras (CoRR, 2024)

fastMRI Breast: A publicly available radial k-space dataset of breast dynamic contrast-enhanced MRI. - Eddy Solomon; Patricia M. Johnson; Zhengguo Tan; Radhika Tibrewala; Yvonne W. Lui; Florian Knoll; Linda Moy; Sungheon Gene Kim; Laura Heacock (CoRR, 2024)

A training regime to learn unified representations from complementary breast imaging modalities. - Umang Sharma; Jungkyu Park 001; Laura Heacock; Sumit Chopra; Krzysztof J. Geras (CoRR, 2024)

An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects. - Jungkyu Park 001; Jakub Chledowski; Stanislaw Jastrzebski; Jan Witowski; Yanqi Xu; Linda Du; Sushma Gaddam; Eric Kim; Alana Lewin; Ujas Parikh; Anastasia Plaunova; Sardius Chen; et al. (IEEE Trans. Medical Imaging, 2024)

A Multi-Modal AI System for Screening Mammography: Integrating 2D and 3D Imaging to Improve Breast Cancer Detection in a Prospective Clinical Study. - Jungkyu Park 001; Jan Witowski; Yanqi Xu; Hari Trivedi; Judy Gichoya; Beatrice Brown-Mulry; Malte Westerhoff; Linda Moy; Laura Heacock; Alana Lewin; Krzysztof J. Geras (CoRR, 2025)