KG
Krzysztof J. Geras
cs.LGcs.CVeess.IVstat.MLBreast NeoplasmsArtificial IntelligenceDeep Learningcs.AIoncologyartificial intelligence
On Valency
published · living versionsW_5352xgra·v1 · currentpublished
fastMRI: An Open Dataset and Benchmarks for Accelerated MRI
with Jure Zbontar, Florian Knoll, Anuroop Sriram, Tullie Murrell +22
1 version
Preprints & journals
61 papers in the corpus · 2015–2026Transcriptome-informed multi-modal AI for predicting neoadjuvant therapy response from breast cancer biopsies2610.03693v1 · Jungkyu Park, Dhruva Biswas, Joseph Cappadona et al.2026 · 0 citationsarXiv
An AI Model Identifies Chemotherapy Benefit in Node-Negative HR+/HER2- Breast Cancer Patients from TAILORx, a Phase 3 Randomized Clinical Trial.42779818 · Chan, Nancy, Tang, Cerise, Biswas, Dhruva et al.2026 · 0 citationsmedRxiv : the preprint server for health sciences. 2026
Causal multi-modal AI for personalized chemosensitivity prediction2609.13567v1 · Dhruva Biswas, Jeroen Berrevoets, Alec McClean et al.2026 · 0 citationsarXiv
Predicting 5-Year Breast Cancer Risk From Longitudinal Digital Breast Tomosynthesis: A Single-Center Retrospective Study.42584410 · Xu, Yanqi, Heacock, Laura, Park, Jungkyu et al.2026 · 1 citationAJR. American journal of roentgenology. 2026
Pitfalls of Administrative Censoring in Survival Models with Time-Indexed Inputs2607.10466v1 · Yanqi Xu, Hui Dai, Carlos Fernandez-Granda et al.2026 · 0 citationsarXiv
Refining Stratification in Premenopausal Node-Positive HR+/HER2- Breast Cancer With a Novel AI-Based Test.42431147 · Elayoubi, Jailan, Tang, Cerise, Ruddy, Kathryn J et al.2026 · 0 citationsClinical breast cancer. 2026;26(8):14-20
Prognostic performance of an AI-based recurrence risk model in clinically low-risk HR+/HER2- early breast cancer10.64898/2026.06.02.26354233v1 · Tang, C., Biswas, D., Liu, C. et al.2026 · 0 citationsmedRxiv
Multi-modal AI for comprehensive breast cancer prognostication.42161927 · Witowski, Jan, Zeng, Ken G, Cappadona, Joseph et al.2026 · 7 citationsNature communications. 2026;17(1)
Analytical Validation of Multimodal AI Test Predicting Breast Cancer Recurrence Risk (Ataraxis Breast RISK).41975736 · Dantone, Marc, Lacsamana, Martin, Zeng, Ken G et al.2026 · 1 citationDiagnostics (Basel, Switzerland). 2026;16(7)
Comparing an AI test to a 21-gene assay for premenopausal node-positive HR+/HER2- breast cancer10.64898/2026.02.06.26345771v1 · Elayoubi, J., Tang, C., Ruddy, K. J. et al.2026 · 1 citationmedRxiv
Prognostic Risk Refinement using Artificial Intelligence in HR+/HER2- Early Breast Cancer: Implications for CDK4/6 Eligibility Criteria10.64898/2026.01.23.26344621v1 · McAndrew, N. P., Ma, C., Davis, A. A. et al.2026 · 1 citationmedRxiv
Robust Disease Prognosis via Diagnostic Knowledge Preservation: A Sequential Learning Approach.41040735 · Rajamohan, Haresh Rengaraj, Xu, Yanqi, Zhu, Weicheng et al.2026 · 1 citationmedRxiv : the preprint server for health sciences. 2025
Meta-Repository of Screening Mammography Classifiers.40776280 · Chłędowski, Jakub, Stadnick, Benjamin, Witowski, Jan et al.2025 · 6 citationsStudies in health technology and informatics. 2025;329:1884-1885
A Multi-Modal AI System for Screening Mammography: Integrating 2D and 3D Imaging to Improve Breast Cancer Detection in a Prospective Clinical Study2504.05636v2 · Jungkyu Park, Jan Witowski, Yanqi Xu et al.2025 · 4 citationsarXiv
A training regime to learn unified representations from complementary breast imaging modalities2408.08560v1 · Umang Sharma, Jungkyu Park, Laura Heacock et al.2024 · 0 citationsarXiv
Understanding differences in applying DETR to natural and medical images2405.17677v2 · Yanqi Xu, Yiqiu Shen, Carlos Fernandez-Granda et al.2024 · 5 citationsMachine.Learning.for.Biomedical.Imaging. 3 (2025)
An Efficient Deep Neural Network to Classify Large 3D Images With Small Objects.37590109 · Park, Jungkyu, Chledowski, Jakub, Jastrzebski, Stanislaw et al.2024 · 13 citationsIEEE transactions on medical imaging. 2024;43(1):351-365
Leveraging Transformers to Improve Breast Cancer Classification and Risk Assessment with Multi-modal and Longitudinal Data2311.03217v2 · Yiqiu Shen, Jungkyu Park, Frank Yeung et al.2023 · 10 citationsarXiv
Leveraging Neural Networks to Profile Health Care Providers with Application to Medicare Claims2309.15316v2 · Wenbo Wu, Fan Li, Richard Liu et al.2023 · 0 citationsarXiv
Improving Information Extraction from Pathology Reports using Named Entity Recognition.37461545 · Zeng, Ken G, Dutt, Tarun, Witowski, Jan et al.2024 · 8 citationsResearch square. 2023
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians.37460754 · Dvijotham, Krishnamurthy Dj, Winkens, Jim, Barsbey, Melih et al.2023 · 124 citationsNature medicine. 2023;29(7):1814-1820
A Competition, Benchmark, Code, and Data for Using Artificial Intelligence to Detect Lesions in Digital Breast Tomosynthesis.36821110 · Konz, Nicholas, Buda, Mateusz, Gu, Hanxue et al.2023 · 33 citationsJAMA network open. 2023;6(2):e230524
Multiple Instance Learning via Iterative Self-Paced Supervised Contrastive Learning2210.09452v2 · Kangning Liu, Weicheng Zhu, Yiqiu Shen et al.2022 · 41 citationsarXiv
An efficient deep neural network to find small objects in large 3D images2210.08645v2 · Jungkyu Park, Jakub Ch\ledowski, Stanis\law Jastrzebski et al.2022 · 1 citationarXiv
Improving breast cancer diagnostics with deep learning for MRI.36170446 · Witowski, Jan, Heacock, Laura, Reig, Beatriu et al.2022 · 140 citationsScience translational medicine. 2022;14(664):eabo4802
MedFuse: Multi-modal fusion with clinical time-series data and chest X-ray images2207.07027v2 · Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout2022 · 30 citationsarXiv
Differences between human and machine perception in medical diagnosis.35477730 · Makino, Taro, Jastrzębski, Stanisław, Oleszkiewicz, Witold et al.2022 · 30 citationsScientific reports. 2022;12(1):6877
Characterizing and overcoming the greedy nature of learning in multi-modal deep neural networks2202.05306v3 · Nan Wu, Stanis\law Jastrzebski, Kyunghyun Cho et al.2022 · 45 citationsarXiv
Estimation of the capillary level input function for dynamic contrast-enhanced MRI of the breast using a deep learning approach.35001423 · Bae, Jonghyun, Huang, Zhengnan, Knoll, Florian et al.2022 · 5 citationsMagnetic resonance in medicine. 2022;87(5):2536-2550
A convolutional neural network for common coordinate registration of high-resolution histology images.34128955 · Daly, Aidan C, Geras, Krzysztof J, Bonneau, Richard2023 · 17 citationsBioinformatics (Oxford, England). 2021;37(22):4216-4226
Towards dynamic multi-modal phenotyping using chest radiographs and physiological data2111.02710v1 · Nasir Hayat, Krzysztof J. Geras, Farah E. Shamout2021 · 0 citationsarXiv
Reducing False-Positive Biopsies using Deep Neural Networks that Utilize both Local and Global Image Context of Screening Mammograms.34731338 · Wu, Nan, Huang, Zhe, Shen, Yiqiu et al.2021 · 12 citationsJournal of digital imaging. 2021;34(6):1414-1423
Artificial intelligence system reduces false-positive findings in the interpretation of breast ultrasound exams.34561440 · Shen, Yiqiu, Shamout, Farah E, Oliver, Jamie R et al.2021 · 270 citationsNature communications. 2021;12(1):5645
Weakly-supervised High-resolution Segmentation of Mammography Images for Breast Cancer Diagnosis.35088055 · Liu, Kangning, Shen, Yiqiu, Wu, Nan et al.2022 · 24 citationsProceedings of machine learning research. 2021;143:268-285
COVID-19 Prognosis via Self-Supervised Representation Learning and Multi-Image Prediction.33469559 · Sriram, Anuroop, Muckley, Matthew, Sinha, Koustuv et al.2023 · 36 citationsArXiv. 2021
Catastrophic Fisher Explosion: Early Phase Fisher Matrix Impacts Generalization2012.14193v3 · Stanislaw Jastrzebski, Devansh Arpit, Oliver Astrand et al.2020 · 17 citationsarXiv
An interpretable classifier for high-resolution breast cancer screening images utilizing weakly supervised localization.33383334 · Shen, Yiqiu, Wu, Nan, Phang, Jason et al.2021 · 209 citationsMedical image analysis. 2021;68:101908
An artificial intelligence system for predicting the deterioration of COVID-19 patients in the emergency department.32793769 · Shamout, Farah E, Shen, Yiqiu, Wu, Nan et al.2023 · 153 citationsArXiv. 2020
How to Implement AI in the Clinical Enterprise: Opportunities and Lessons Learned.33153543 · Lui, Yvonne W, Geras, Krzysztof, Block, K Tobias et al.2021 · 15 citationsJournal of the American College of Radiology : JACR. 2020;17(11):1394-1397
Investigating and Simplifying Masking-based Saliency Methods for Model Interpretability2010.09750v1 · Jason Phang, Jungkyu Park, Krzysztof J. Geras2020 · 4 citationsarXiv
Reducing false-positive biopsies with deep neural networks that utilize local and global information in screening mammograms2009.09282v1 · Nan Wu, Zhe Huang, Yiqiu Shen et al.2020 · 2 citationsarXiv
Prediction of Total Knee Replacement and Diagnosis of Osteoarthritis by Using Deep Learning on Knee Radiographs: Data from the Osteoarthritis Initiative.32573386 · Leung, Kevin, Zhang, Bofei, Tan, Jimin et al.2020 · 238 citationsRadiology. 2020;296(3):584-593
Understanding the robustness of deep neural network classifiers for breast cancer screening2003.10041v1 · Witold Oleszkiewicz, Taro Makino, Stanis\law Jastrzebski et al.2020 · 0 citationsarXiv
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms.32119094 · Schaffter, Thomas, Buist, Diana S M, Lee, Christoph I et al.2020 · 410 citationsJAMA network open. 2020;3(3):e200265
The Break-Even Point on Optimization Trajectories of Deep Neural Networks2002.09572v1 · Stanislaw Jastrzebski, Maciej Szymczak, Stanislav Fort et al.2020 · 40 citationsarXiv
fastMRI: A Publicly Available Raw k-Space and DICOM Dataset of Knee Images for Accelerated MR Image Reconstruction Using Machine Learning.32076662 · Knoll, Florian, Zbontar, Jure, Sriram, Anuroop et al.2021 · 416 citationsRadiology. Artificial intelligence. 2020;2(1):e190007
Artificial Intelligence Explained for Nonexperts.31991447 · Razavian, Narges, Knoll, Florian, Geras, Krzysztof J2020 · 28 citationsSeminars in musculoskeletal radiology. 2020;24(1):3-11
Deep Neural Networks Improve Radiologists' Performance in Breast Cancer Screening.31603772 · Wu, Nan, Phang, Jason, Park, Jungkyu et al.2021 · 693 citationsIEEE transactions on medical imaging. 2020;39(4):1184-1194
Globally-Aware Multiple Instance Classifier for Breast Cancer Screening.32149282 · Shen, Yiqiu, Wu, Nan, Phang, Jason et al.2024 · 34 citationsMachine learning in medical imaging. MLMI (Workshop). 2019;11861:18-26
Artificial Intelligence for Mammography and Digital Breast Tomosynthesis: Current Concepts and Future Perspectives.31549948 · Geras, Krzysztof J, Mann, Ritse M, Moy, Linda2020 · 296 citationsRadiology. 2019;293(2):246-259
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