Search Results for author: Jungkyu Park

Found 11 papers, 5 papers with code

A training regime to learn unified representations from complementary breast imaging modalities

no code implementations16 Aug 2024 Umang Sharma, Jungkyu Park, Laura Heacock, Sumit Chopra, Krzysztof Geras

Full Field Digital Mammograms (FFDMs) and Digital Breast Tomosynthesis (DBT) are the two most widely used imaging modalities for breast cancer screening.

Lesion Detection

An efficient deep neural network to find small objects in large 3D images

1 code implementation16 Oct 2022 Jungkyu Park, Jakub Chłędowski, Stanisław Jastrzębski, Jan Witowski, Yanqi Xu, Linda Du, Sushma Gaddam, Eric Kim, Alana Lewin, Ujas Parikh, Anastasia Plaunova, Sardius Chen, Alexandra Millet, James Park, Kristine Pysarenko, Shalin Patel, Julia Goldberg, Melanie Wegener, Linda Moy, Laura Heacock, Beatriu Reig, Krzysztof J. Geras

On a dataset collected at NYU Langone Health, including 85, 526 patients with full-field 2D mammography (FFDM), synthetic 2D mammography, and 3D mammography, 3D-GMIC achieves an AUC of 0. 831 (95% CI: 0. 769-0. 887) in classifying breasts with malignant findings using 3D mammography.

Anatomy

Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability

1 code implementation19 Oct 2020 Jason Phang, Jungkyu Park, Krzysztof J. Geras

We find that the most important ingredients for high quality saliency map generation are (1) using both masked-in and masked-out objectives and (2) training the classifier alongside the masking model.

counterfactual

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

no code implementations19 Sep 2020 Nan Wu, Zhe Huang, Yiqiu Shen, Jungkyu Park, Jason Phang, Taro Makino, S. Gene Kim, Kyunghyun Cho, Laura Heacock, Linda Moy, Krzysztof J. Geras

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.

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

1 code implementation4 Aug 2020 Farah E. Shamout, Yiqiu Shen, Nan Wu, Aakash Kaku, Jungkyu Park, Taro Makino, Stanisław Jastrzębski, Duo Wang, Ben Zhang, Siddhant Dogra, Meng Cao, Narges Razavian, David Kudlowitz, Lea Azour, William Moore, Yvonne W. Lui, Yindalon Aphinyanaphongs, Carlos Fernandez-Granda, Krzysztof J. Geras

In order to verify performance in a real clinical setting, we silently deployed a preliminary version of the deep neural network at New York University Langone Health during the first wave of the pandemic, which produced accurate predictions in real-time.

COVID-19 Diagnosis Decision Making +2

Screening Mammogram Classification with Prior Exams

no code implementations30 Jul 2019 Jungkyu Park, Jason Phang, Yiqiu Shen, Nan Wu, S. Gene Kim, Linda Moy, Kyunghyun Cho, Krzysztof J. Geras

Radiologists typically compare a patient's most recent breast cancer screening exam to their previous ones in making informed diagnoses.

Classification General Classification

Cannot find the paper you are looking for? You can Submit a new open access paper.