Shandong Wu

1. Shandong Wu, Susan P. Weinstein, Michael J DeLeo III, Emily F. Conant, Jinbo Chen, Susan M. Domchek, Despina Kontos, Quantitative assessment of Background Parenchymal Enhancement in breast MRI predicts response to Risk-Reducing Salpingo-Oophorectomy: Preliminary evaluation in a cohort of BRCA1/2 mutation carriers, Breast Cancer Research, 17(1):67-77, May 2015.
2. Sarah S. Aboutalib, Aly A. Mohamed, Wendie A. Berg, Margarita L. Zuley, Jules H. Sumkin, Shandong Wu, Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening, Clinical Cancer Research, 24(23):5902-5909. 2018 Dec 1; doi: 10.1158/1078-0432.CCR-18-1115. Epub 2018 Oct 11.
3. Long Gao and Shandong Wu, Response Score of Deep Learning for Out-of-Distribution Sample Detection of Medical Images, Journal of Biomedical Informatics, 2020 Jul;107:103442. Doi: 10.1016/j.jbi.2020.103442. Epub 2020 May 22.
4. Long Gao, Lei Zhang, Chang Liu, Shandong Wu, Handling Imbalanced Medical Image Data: A Deep-Learning-Based One-Class Classification Approach, Artificial Intelligence in Medicine, 2020 Aug;108:101935. Doi: 10.1016/j.artmed.2020.101935. Epub 2020 Aug 7.
5. Kadie Clancy, Esmaeel Reza Dadashzadeh, Robert Handzel, Caroline Rieser, JB Moses, Lauren Rosenblum, Shandong Wu, Machine Learning for the Prediction of Pathologic Pneumatosis Intestinalis, Surgery, March 24, 2021, Available Online,
6. Qianwei Zhou, Margarita Zuley, Yuan Guo, Lu Yang, Bronwyn Nair, Adrienne Vargo, Suzanne Ghannam, Dooman Arefan, Shandong Wu, A machine and human reader study on AI diagnosis model safety under attacks of adversarial images, Nature Communications, 2021 Dec 14;12(1):7281. Doi: 10.1038/s41467-021-27577-x.
7. Constance Lehman and Shandong Wu, Stargazing through the lens of AI in Clinical Oncology, Nature Cancer 2, 1265–1267 (Dec 21, 2021).
8. Degan Hao, Qiong Li, Qiu-Xia Feng, Liang Qi, Xi-Sheng Liu, Dooman Arefan, Yu-Dong Zhang, Shandong Wu, Identifying prognostic markers from clinical, radiomics, and deep learning imaging features for gastric cancer survival prediction, Frontiers in Oncology, Vol. 11, Feb. 2022.
9. Matthew Pease, Dooman Arefan, Jason Barber, Esther Yuh, Ava Puccio, Kerri Hochberger, Enyinna Nwachuku, Souvik Roy, Stephanie Casillo, Nancy Temkin, David Okonkwo, Shandong Wu, Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans, Radiology, 2022 Aug;304(2):385-394. Doi: 10.1148/radiol.212181.
10. Jonathan Elmer, Chang Liu, Matthew Pease, Dooman Arefan, Patrick J. Coppler, Katharyn Flickinger, Joseph M. Mettenburg, Maria E. Baldwin, Niravkumar Barot, and Shandong Wu, Deep learning of early brain imaging to predict post-arrest electroencephalography, Resuscitation, Vol. 172, March 2022, Pages 17-23
11. Degan Hao, Maaz Ahsan, Tariq Salim, Andres Duarte-Rojo, Dadashzadeh Esmaeel, Yudong Zhang, Dooman Arefan and Shandong Wu, A self-training teacher-student model with an automatic label grader for abdominal skeletal muscle segmentation, Artificial Intelligence In Medicine, volume 132, October 2022, 102366.
12. Saba Dadsetan, Dooman Arefan, Wendie A. Berg, Margarita L. Zuley, Jules, H. Sumkin, Shandong Wu, Deep Learning of Longitudinal Mammogram Examinations for Breast Cancer Risk Prediction, Pattern Recognition, Volume 132, December 2022, 108919.
13. Haotian Sun, Shandong Wu, Xinjian Chen, Ming Li, Lingji Kong, Xiaodong Yang, You Meng, Shuangqing Chen, and Jian Zheng, SAH-NET: Structure-Aware Hierarchical Network for Clustered Microcalcification Classification in Digital Breast Tomosynthesis, IEEE Transactions on Cybernetics, 2022 Oct 20;PP. doi: 10.1109/TCYB.2022.3211499.
14. Degan Hao, Qiong Li, Qiu-Xia Feng, Liang Qi, Xi-Sheng Liu, Dooman Arefan, Yu-Dong Zhang, Shandong Wu, SurvivalCNN: A Deep Learning-based Method for Gastric Cancer Survival Prediction using Radiological Imaging Data and Clinicopathological Variables, Artificial Intelligence In Medicine, Volume 134, December 2022, 102424.
15. Chang Liu, Jonathan Elmer, Dooman Arefan, Matthew Pease, Shandong Wu, Interpretable machine learning model for imaging-based outcome prediction after cardiac arrest, Resuscitation, 2023 Jul 4;109894. Doi: 10.1016/j.resuscitation.2023.109894.
16. Dooman Arefan, Margarita Zuley, Wendie Berg, Lu Yang, Jules Sumkin, Shandong Wu, Assessment of Background Parenchymal Enhancement at Dynamic Contrast-enhanced MRI in Predicting Breast Cancer Recurrence Risk, Radiology, 2024 Jan;310(1):e230269,
17. Chang Liu, Min Sun, Dooman Arefan, Margarita Zuley, Jules Sumkin, Shandong Wu, Deep learning of mammogram images to reduce unnecessary breast biopsies: A preliminary study, Breast Cancer Research, 2024 May 24; 26(1): 82. Doi: 10.1186/s13058-024-01830-9.
18. Shandong Wu, Brian E. Moore, and Mubarak Shah, “Chaotic Invariants of Lagrangian Particle Trajectories for Anomaly Detection in Crowded Scenes,” IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2010), San Francisco, CA, USA, June 13-18, 2010.
19. Shandong Wu, Omar Oreifej, Mubarak Shah, “Action Recognition in Videos Acquired by a Moving Camera Using Motion Decomposition of Lagrangian Particle Trajectories,” International Conference on Computer Vision (ICCV2011), Barcelona, Spain, 6-13 Nov. 2011.
20. Shandong Wu, Susan P. Weinstein, and Despina Kontos, “Atlas-Based Probabilistic Fibroglandular Tissue Segmentation in Breast MRI,” Medical Image Computing & Computer-Assisted Intervention (MICCAI), Part II, Lecture Notes in Computer Science (LNCS) 7511, pp. 437-445. H. Delingette, P. Golland, K. Mori (eds.). Springer-Verlag Berlin Heidelberg, 2012.
21. Giacomo Nebbia, Saba Dadsetan, Dooman Arefan, Margarita L. Zuley, Jules H. Sumkin, Heng Huang, Shandong Wu, Radiomics-Informed Deep Curriculum Learning for Breast Cancer Diagnosis. In: de Bruijne M. et al. (eds) Medical Image Computing and Computer Assisted Intervention – MICCAI 2021. MICCAI 2021. Lecture Notes in Computer Science, vol 12905. Springer, Cham.
22. Jun Luo, Shandong Wu, Adapt to Adaptation: Learning Personalization for Cross-Silo Federated Learning, the 31st International Joint Conference on Artificial Intelligence (IJCAI), July 23-29, 2022, Vienna, Austria
23. Jun Luo, Matias Mendieta, Chen Chen, Shandong Wu, PGFed: Personalize Each Client’s Global Objective for Federated Learning, IEEE/CVF International Conference on Computer Vision, Oct. 2-6, 2023, Paris, France (Oral Presentation)
24. Zhengbo Zhou, Dooman Arefan, Margarita Zuley, Degan Hao, Jules Sumkin, Shandong Wu, Knowledge-guided multi-task learning for breast cancer diagnosis using longitudinal mammogram images, IEEE International Symposium on Biomedical Imaging (ISBI) 2024, 27-30 May 2024, Athens, Greece. (Oral presentation)
25. Jun Luo, Chen Chen, Shandong Wu, Mixture of Experts Made Personalized: Federated Prompt Learning for Vision-Language Models, The Thirteenth International Conference on Learning Representations (ICLR), Apr. 24 – 28, 2025, Singapore.