Dalian University of Technology

Publications

See Google Scholar for a complete chronological list of papers.

Highlighted

When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
Hongming Xu, Mingkang Wang, Duanbo Shi, Huamin Qin, Yunpeng Zhang, Zaiyi Liu, Anant Madabhushi, Peng Gao, Fengyu Cong, Cheng Lu
Medical Image Analysis   ·   01 Apr 2025   ·   doi:10.1016/j.media.2025.103456
Foundation models Computational pathology Multiple instance learning
ODA-GAN:Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining
ODA-GAN:Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining
Tong Wang, Mingkang Wang, Zhongze Wang, Hongkai Wang, Qi Xu, Fengyu Cong, Hongming Xu
Conference on Computer Vision and Pattern Recognition (CVPR 2025)   ·   16 Jun 2025   ·   Coming soon
Virtual Staining Generative Adversarial Network Domain Adapation

Selected

2025

ODA-GAN:Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining
ODA-GAN:Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining
Tong Wang, Mingkang Wang, Zhongze Wang, Hongkai Wang, Qi Xu, Fengyu Cong, Hongming Xu
Conference on Computer Vision and Pattern Recognition (CVPR 2025)   ·   16 Jun 2025   ·   Coming soon
Virtual Staining Generative Adversarial Network Domain Adapation
When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
When multiple instance learning meets foundation models: Advancing histological whole slide image analysis
Hongming Xu, Mingkang Wang, Duanbo Shi, Huamin Qin, Yunpeng Zhang, Zaiyi Liu, Anant Madabhushi, Peng Gao, Fengyu Cong, Cheng Lu
Medical Image Analysis   ·   01 Apr 2025   ·   doi:10.1016/j.media.2025.103456
Foundation models Computational pathology Multiple instance learning

2024

Multi-Task Adaptive Resolution Network for Lymph Node Metastasis Diagnosis From Whole Slide Images of Colorectal Cancer
Multi-Task Adaptive Resolution Network for Lymph Node Metastasis Diagnosis From Whole Slide Images of Colorectal Cancer
Tong Wang, Su-Jin Shin, Mingkang Wang, Qi Xu, Guiyang Jiang, Fengyu Cong, Jeonghyun Kang, Hongming Xu
IEEE Journal of Biomedical and Health Informatics   ·   24 Oct 2024   ·   doi:10.1109/JBHI.2024.3485703
Computational pathology Multi task learning
Double-Tier Attention Based Multi-label Learning Network for Predicting Biomarkers from Whole Slide Images of Breast Cancer
Double-Tier Attention Based Multi-label Learning Network for Predicting Biomarkers from Whole Slide Images of Breast Cancer
Mingkang Wang, Tong Wang, Fengyu Cong, Cheng Lu, Hongming Xu
Medical Image Computing and Computer Assisted Intervention (MICCAI 2024)   ·   03 Oct 2024   ·   doi:10.1007/978-3-031-72378-0_9
Computational pathology Multiple instance learning

ALL

First auhor/corresonding author Publications

#Co-first authors, * Corresponding authors

Journal Papers

  1. Hongming Xu#, Mingkang Wang, Duanbo Shi, Huamin Qin, Yunpeng Zhang, Zaiyi Liu, Anant Madabhushi, Peng Gao, Fengyu Cong, Cheng Lu*. "When multiple instance learning meets foundation models: Advancing histological whole slide image analysis". Medical Image Analysis (MedIA), pp.103456, 2025 (2023 IF: 10.7) (中科院1区-Top).
  2. Tong Wang#, Su-Jin Shin#, Mingkang Wang, Qi Xu, Guiyang Jiang, Fengyu Cong, Jeonghyun Kang, Hongming Xu*. "Multi-task Adaptive Resolution Network for Lymph Node Metastasis Diagnosis from Whole Slide Images of Colorectal Cancer". IEEE Journal of Biomedical and Health Informatics (JBHI) , vol.29, no.1, pp.420-432, 2025 (2023 IF: 6.7) (中科院1区-Top).
  3. Shan Jin, Hongming Xu*, Yue Dong, Xiaofeng Wang, Xinyu Hao, Fengying Qin, Ranran Wang, Fengyu Cong. "Ranking attention multiple instance learning for lymph node metastasis prediction on multicenter cervical cancer MRI". Journal of Applied Clinical Medical Physics, e14547, 2024 (2023 IF: 2.0).
  4. Xinyu Hao, Hongming Xu*, Nannan Zhao, Tao Yu, Timo Hamalainenc, Fengyu Cong. "Predicting pathological complete response based on weakly and semi-supervised joint learning in breast cancer multi-parametric MRI". Biomedical Signal Processing and Control (BSPC), 93 (2024): 106164 (2022 IF: 5.1) (中科院2区).
  5. Ranran Wang, Yusong Qiu, Xinyu Hao, Shan Jin, Junxiu Gao, Heng Qi, Qi Xu, Yong Zhang*, Hongming Xu*. "Simultaneously segmenting and classifying cell nuclei by using multi-task learning in multiplex immunohistochemical tissue microarray sections". Biomedical Signal Processing and Control (BSPC), 93 (2024): 106143 (2022 IF: 5.1) (中科院2区).
  6. Ranran Wang, Yusong Qiu, Tong Wang, Mingkang Wang, Shan Jin, Fengyu Cong, Yong Zhang*, Hongming Xu*. "MIHIC: A multiplex IHC histopathological image classification dataset for lung cancer immune microenvironment quantification". Frontiers in Immunology, 15 (2024): 1334348 (2022 IF: 7.3) (中科院2区).
  7. Hongming Xu, Qi Xu, Fengyu Cong, Jeonghyun Kang, Chu Han, Zaiyi Liu, Anant Madabhushi, Cheng Lu. "Vision Transformers for Computational Histopathology". IEEE Reviews in Biomedical Engineering (RBME), vol.17, pp.63-79, 2024 (2022 IF: 17.6) (中科院1区-Top, ESI Highly Cited Paper).
  8. Xinyu Hao, Dongying Zheng, Muhanmmad Khan, Lixia Wang, Timo Hamalainen, Fengyu Cong, Hongming Xu*, Kedong Song*. "Machine learning models for predicting adverse pregnancy outcomes in pregnant women with systemic lupus erythematosous". Diagnostics, 13, no. 4 (2023): 612 (2022 IF: 3.6).
  9. Shan Jin, Hongming Xu*, Yue Dong, Xinyu Hao, Fengying Qin, Qi Xu, Yong Zhu, Fengyu Cong. "Automatic cervical cancer segmentation in multimodal MRI using an EfficientNet encoder in UNet++ architecture". International Journal of Imaging Systems and Technology, vol.33, pp.362-377, 2023 (2022 IF: 3.3).
  10. Hongming Xu, Sunho Park, Jean R. Clemenceau, Jinhwan Choi, Sung Hak Lee, Tae Hyun Hwang. "Spatial heterogeneity and organization of tumor mutation burden with immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer". Journal of Pathology Informatics, vol.13, pp.100105, 2022.
  11. Hongming Xu, Yoon Jin Cha, Jean R. Clemenceau, Jinhwan Choi, Sung Hak Lee, Jeonghyun Kang, Tae Hyun Hwang. "Spatial analysis of tumor infiltrating lymphocytes in histological sections using deep learning techniques predicts progression-free survival in colorectal carcinoma". The Journal of Pathology: Clinical Research, vol.8, no.4, pp.327-339, 2022 (2021 IF: 4.373) (中科院病理学1区-Top).
  12. Hongming Xu, Lina Liu, Xiujuan Lei, Mrinal Mandal, Cheng Lu. "An Unsupervised Method for Histological Image Segmentation based on Tissue Cluster Level Graph Cut". Computerized Medical Imaging and Graphics (CMIG), vol.93, pp.101974, August 2021 (2021 IF: 7.422) (中科院2区).
  13. Hongming Xu, Fengyu Cong, Tae Hyun Hwang. "Machine Learning and Artificial Intelligence–driven Spatial Analysis of the Tumor Immune Microenvironment in Pathology Slides". European Urology Focus, vol.7, no.4, pp.706-709, August 2021 (2021 IF: 5.952). - Invited Mini-Review Paper (中科院1区-Top).
  14. Hongming Xu, Sunho Park, Tae Hyun Hwang. "Computerized classification of prostate cancer Gleason scores from whole slide images". IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB), vol.17, no.6, pp.1871-1882, 2020 (IF: 3.371). - Recommended to be published as the top-3 oral papers in BioKDD workshop 2018 (CCF-B).
  15. Hongming Xu, Cheng Lu, Richard Berendt, Naresh Jha, Mrinal Mandal. "Automated analysis and classification of melanocytic tumor on skin whole slide images". Computerized Medical Imaging and Graphics (CMIG), vol. 66, pp. 124-134, 2018 (IF: 4.79) (中科院2区).
  16. Hongming Xu, Cheng Lu, Richard Berendt, Naresh Jha, Mrinal Mandal. "Automatic nuclear segmentation using multi-scale radial line scanning with dynamic programming". IEEE Transactions on Biomedical Engineering (TBME), vol. 64, no. 10, pp. 2475-2485, 2017 (IF: 4.538) (中科院2区).
  17. Hongming Xu, Cheng Lu, Richard Berendt, Naresh Jha, Mrinal Mandal. "Automatic nuclei detection based on generalized Laplacian of Gaussian Filters". IEEE Journal of Biomedical and Health Informatics (JBHI), vol. 21, no. 3, pp. 826-837, 2017 (IF: 5.772) (中科院1区-Top).
  18. Hongming Xu, Richard Berendt, Naresh Jha, Mrinal Mandal. "Automatic measurement of melanoma depth of invasion in skin histopathological images". Micron, vol. 97, pp. 56-67, 2017 (IF: 2.251).
  19. Hongming Xu, Mrinal Mandal. "Epidermis segmentation in skin histopathological images based on thickness measurement and k-means algorithm". EURASIP Journal on Image and Video Processing, vol. 2015, no. 1, pp. 1-14, 2015 (IF: 1.789).
  20. Hongming Xu, Cheng Lu, Mrinal Mandal. "An efficient technique for nuclei segmentation based on ellipse descriptor analysis and improved seed detection algorithm". IEEE Journal of Biomedical and Health Informatics (JBHI), vol. 18, no. 5, pp. 1729-1741, 2014 (IF: 5.772) (中科院1区-Top).

Conference Papers

  1. Qibin Zhang, Xinyu Hao, Qiao Chen, Rui Xu, Fengyu Cong, Cheng Lu*, and Hongming Xu*. "Multi-modal Knowledge Decomposition based Online Distillation for Biomarker Prediction in Breast Cancer Histopathology". Accepted by International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025 (CCF-B，医学图像处理顶会).
  2. Xinyu Hao, Hongming Xu*, Qibin Zhang, Qi Xu, Ilkka Polonen, and Fengyu Cong. "Dual Selective Gleason Pattern-Aware Multiple Instance Learning for Grade Group Prediction in Histopathology Images". Accepted by International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025 (CCF-B，医学图像处理顶会).
  3. Xinyu Hao, Hongming Xu*, Qibin Zhang, Qi Xu, Ilkka Polonen, and Fengyu Cong. "Predicting Radiation Therapy Response based on Dynamic Temporal Feature Difference Fusion from Longitudinal MRI". Accepted by International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), 2025 (CCF-B，医学图像处理顶会).
  4. Tong Wang, Mingkang Wang, Zhongze Wang, Hongkai Wang, Qi Xu, Fengyu Cong, and Hongming Xu*. "ODA-GAN:Orthogonal Decoupling Alignment GAN Assisted by Weakly-supervised Learning for Virtual Immunohistochemistry Staining". Proceedings of the Computer Vision and Pattern Recognition Conference (CVPR), pp. 25920-25929, 2025 (CCF-A，CV领域顶会).
  5. Qiao Chen, Hongming Xu*, Xinyu Hao, Qibin Zhang, Huamin Qin, Tommi Karkkainen, and Fengyu Cong. "Distilling Genomic Knowledge into Whole Slide Imaging for Glioma Molecular Classification". Accepted by the 38th IEEE International Symposium on Computer-Based Medical Systems (CBMS), 2025
  6. Hongbo Liu, Hongming Xu*, Xinyu Hao, Mingliang Zhang, Cheng Lu, Ilkka, Polonen, and Fengyu Cong. "UNI-HoverNet: nuclei segmentation and classification across diverse tissue sections based on the UNI foundation model". Accepted by the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025
  7. Shan Jin, Hongming Xu*, Yanmei Zhu, Xiaozhuo Gao, Mingkang Wang, and Fengyu Cong. "Multi-Scale Multiple Instance Learning for Lymph Node Metastasis Prediction in Early Gastric Cancer". Accepted by the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025
  8. Xiaorui Ma, Hongming Xu*, Ranran Wang, Liqun Zhang, and Jingdong Zhang. "Predicting the efficacy of first-line therapy for patients with colorectal cancer liver metastases using CT imaging and clinical data". Accepted by the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025
  9. Xinyu Hao, Hongming Xu*, Hongbo Liu, Timo Hamalainen, and Fengyu Cong. "Immunohistochemical information integrated pre-training improves HER2 status prediction from whole slide images of breast cancer". Accepted by the 47th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2025
  10. Mingkang Wang, Tong Wang, Fengyu Cong, Cheng Lu*, Hongming Xu*. "Double-tier Attention based Multi-label Learning Network for Predicting Biomarkers from Whole Slide Images of Breast Cancer". International Conference on Medical Image Computing and Computer-Assisted Intervention (MICCAI), pp. 91-101, 2024 (CCF-B，医学图像处理顶会).
  11. Yali Wang, Haochun Shi, Xingye Qiao, Mingkang Wang, Fengyu Cong, Yanbin Zhao, Hongming Xu*. "Benchmarking Deep Learning Models for Zebrafish Ventricle Segmentation". In 4th International Conference on Image, Vision and Intelligent Systems (ICIVIS), pp. xx, 2024.
  12. Qiao Chen, Hongming Xu*, Huamin Qin, Xinyu Hao, Shan Jin, Timo Hämäläinen, Fengyu Cong. "Comparative Validation of Graph Neural Networks for Glioma Grading in Whole Slide Images". In 4th International Conference on Image, Vision and Intelligent Systems (ICIVIS), pp. xx, 2024.
  13. Junxiu Gao, Shan Jin, Ranran Wang, Mingkang Wang, Tong Wang, Hongming Xu*. "Dual-stream Context-aware Neural Network for Survival Prediction from Whole Slide Images". In Chinese Conference on Pattern Recognition and Computer Vision (PRCV), pp.3-14, 2023 (CCF-C类, Acceptance rate: 37.95%).
  14. Junxiu Gao, Xinyu Hao, Shan Jin, Hongming Xu*. “Self-supervised contrastive pre-training integrated with multi-level co-attention for survival prognosis from whole slide images”. In 3rd International Conference on Image, Vision and Intelligent Systems (ICIVIS), pp. 650-658, 2023.
  15. Xinyu Hao, Hongming Xu*, Zhao Nannan, Yu Tao, Hamalainen Timo, Fengyu Cong. "Predicting pathological complete response based on weakly and semi-supervised joint learning from breast cancer MRI". In 45th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 1-4, 2023.
  16. Ranran Wang, Yusong Qiu, Yong Zhang, Hongming Xu*. "SRSA-Net: Separable ResUnit and Self-Attention optimized network for simultaneous nuclei segmentation and classification in histology images". In Asian-Pacific Conference on Medical and Biological Engineering, pp. 105-112, 2023.
  17. Shan Jin, Hongming Xu*, Yue Dong, Xinyu Hao, Fengying Qin, Ranran Wang, Fengyu Cong. "Multiple instance learning for lymph node metastasis prediction from cervical cancer MRI". In 20th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 1-4, 2023.
  18. Hongming Xu, Tae Hyun Hwang. "Statistical Local Binary Patterns (SLBP): application to prostate cancer Gleason score prediction from whole slide pathology images". In 16th IEEE International Symposium on Biomedical Imaging (ISBI), pp. 895-899, 2019.
  19. Hongming Xu, Huiquan Wang, Richard Berendt, Naresh Jha, Mrinal Mandal. "Computerized measurement of melanoma depth of invasion in skin biopsy images". In 2017 International Conference on Biomedical and Health Informatics (BHI), pp. 17-20, 2017 (Acceptance Rate: 38%).
  20. Hongming Xu, Huiquan Wang, Richard Berendt, Naresh Jha, Mrinal Mandal. "Automated nuclear segmentation in skin histopathological images using multi-scale radial line scanning". In IEEE-NIH Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies, pp. 175-178, 2016.
  21. Hongming Xu, Mrinal Mandal. "Eficient segmentation of skin epidermis in whole slide histopathological images". In Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3869-3872, 2015.
  22. Hongming Xu, Cheng Lu, Mrinal Mandal. "Automated segmentation of regions of interest in whole slide skin histopathological images". In Proceedings of 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), pp. 3855-3858, 2015.

Book Chapters

  1. Salah Alheejawi, Mrinal Mandal, Hongming Xu, Cheng Lu, Richard Berendt and Naresh Jha. "Deep learning based histopathological image analysis for automated detection and staging of melanoma". Book Chapter in Deep Learning Techniques for Biomedical and Health Informatics, pp. 237-265, Chapter 10, Springer, 2020.

Co-auhor Publications

Journal Papers

  1. Dongdong Zhou, Qi Xu, Jiacheng Zhang, Lei Wu, Hongming Xu, Lauri Kettunen, Zheng Chang, Qiang Zhang, Fengyu Cong. "Interpretable Sleep Stage Classification Based on Layer-wise Relevance Propagation". IEEE Transactions on Instrumentation and Measurement, vol.73, pp.3511710, 2024 (2022 IF: 5.6) (中科院2区).
  2. Qin, Fengying, Xinyan Sun, Mingke Tian, Shan Jin, Jian Yu, Jing Song, Feng Wen, Hongming Xu, Tao Yu, Yue Dong. "Prediction of lymph node metastasis in operable cervical cancer using clinical parameters and deep learning with MRI data: a multicentre study". Insights into Imaging, vo.15, no.1, pp.1-14, 2024 (2022 IF: 4.7) (中科院2区).
  3. Qin, Fengying, Huiting Pang, Jintao Ma, Hongming Xu, Tao Yu, Yahong Luo, Yue Dong. "The value of multiparametric MRI combined with clinical prognostic parameters in predicting the 5-year survival of stage IIIC1 cervical squamous cell carcinoma". European Journal of Radiology, pp.111181, 2023 (2022 IF: 3.3).
  4. Md. Ziaul Hoque, Anja Keskinarkaus, Pia Nyberg, Hongming Xu, Tapio Seppänena. "Invasion Depth Estimation of Carcinoma Cells using Adaptive Stain Normalization to Improve Epidermis Segmentation Accuracy". Computerized Medical Imaging and Graphics (CMIG), vol.108, pp.102276, 2023 (2022 IF: 5.7) (中科院2区).
  5. Dongdong Zhou, Qi Xu, Jian Wang, Hongming Xu, Lauri Kettunen, Zheng Chang, Fengyu Cong. "Alleviating Class Imbalance Problem in Automatic Sleep Stage Classification". IEEE Transactions on Instrumentation and Measurement, vol.71, pp.1-12, 2022 (2022 IF: 5.6) (中科院2区).
  6. Jeonghyun Kang, Jae-hoon Lee, Hye-Sun Lee, Eun-Suk Cho, Eun Jung Park, Seung Hyuk Baik, Kang Young Lee, Chihyun Park, Yunku Yeu, Jean Clemenceau, Sunho Park, Hongming Xu, Changjin Hong, Tae Hyun Hwang. "Radiomics Features of F-fluorodeoxyglucose Positron-Emission Tomography as a Novel Prognostic Signature in Colorectal Cancer". Cancers, vol.13, no.3, pp.392, 2021 (IF: 6.636) (中科院2区).
  7. Salah Alheejaw, Hongming Xu, Richard Berendt, Naresh Jha, Mrinal Mandal. "Novel lymph node segmentation and proliferation index measurement for skin melanoma biopsy images". Computerized Medical Imaging and Graphics (CMIG), vol. 73, pp. 19-29, 2019 (IF: 4.79) (中科院2区).
  8. Cheng Lu, Hongming Xu, Jun Xu, Hannah Gilmore, Mrinal Mandal, Anant Madabhushi. "Multi-pass adaptive voting for nuclei detection in histopathological Images". Scientific Reports, vol. 6, sp. 33985, 2016 (IF: 4.379).

Conference Papers

  1. Wei Miao, Jiangrong Shen, Hongming Xu, Tommi Kärkkäinen, Qi Xu, Yi Xu, Fengyu Cong. "Advanced SpikingYOLOX: Extending Spiking Neural Network on Object Detection with Spike-based Partial Self-Attention and 2D-Spiking Transformer". Accepted by ACM Multimedia, 2025 (CCF-A类).
  2. Yaxin Li, Qi Xu, Jiangrong Shen, Hongming Xu, Long Chen, Gang Pan. "Towards efficient deep spiking neural networks construction with spiking activity based pruning". Proceedings of the 41st International Conference on Machine Learning (ICML), pp. 29063 - 29073, 2024 (CCF-A类).
  3. Huiquan Wang, S. Nizam Ahmed, Hongming Xu, Mrinal Mandal. “Automated detection of cavernous malformations in Brain MRI images”. In 8th International IEEE EMBS Conference on Neural Engineering, pp.17-20, 2017.
  4. Huiquan Wang, Hongming Xu, S. Nizam Ahmed, Mrinal Mandal. “Computer aided detection of cavernous malformation in T2-weighted brain MR images”. In IEEE-NIH Special Topics Conference on Healthcare Innovations and Point-of-Care Technologies, pp. 101–104, 2016.

Conference Abstracts

  1. Hongming Xu, Yoon Jin Cha, Jean R. Clemenceau, Jinhwan Choi, Sung Hak Lee, Jeonghyun Kang, and Tae Hyun Hwang Tae Hyun Hwang. "Spatial analysis of tumor infiltrating lymphocytes based on deep learning using histopathology image to predict progression-free survival in colorectal cancer".American Association for Cancer Research Annual Meeting (AACR), April 2022 (selected as the Oral Presentation)
  2. Hongming Xu, Sung Hak Lee and Tae Hyun Hwang. "Transfer learning for tumor mutation burden prediction and spatial heterogeneity analysis from histopathology slides in bladder cancer". American Association for Cancer Research Annual Meeting (AACR), June 2020
  3. Isaiah S. Pressman, Hongming Xu, Jeonghyun Kang, Yoon Jin Cha, Sung Hak Lee and Tae Hyun Hwang. "Deep learning can predict microsatellite instability from histology in colorectal cancer across different ethnic groups". American Association for Cancer Research Annual Meeting (AACR), June 2020
  4. Sunho Park, Saehoon Kim, Hongming Xu and Tae Hyun Hwang. "Deep Gaussian processes for weakly supervised learning: tumor mutation burden (TMB) prediction". Bayesian Deep Learning NeurIPS 2019 Workshop, Dec 2019
  5. Hongming Xu, Sunho Park and Tae Hyun Hwang. "Automatic classification of prostate cancer Gleason scores from digitized whole slide tissue biopsies". In 17th International Workshop on Data Mining in Bioinformatics (BioKDD), August, 2018. (The top-3 oral presentations in BioKDD and poster award, and poster presentation in KDD 2018)
  6. Hongming Xu, Sunho Park, Sung Hak Lee and Tae Hyun Hwang. "Using transfer learning on whole slide images to predict tumor mutational burden in bladder cancer patients". In 5th Digital Pathology AI Congress: USA, June 2019
  7. Hongming Xu and Tae Hyun Hwang. "Machine learning for classification of prostate cancer Gleason scores from digitized whole slide tissue biopsies". In 38th Annual Cleveland Clinic Research Day, Sep 2018
  8. Salah Alheejawi, Hongming Xu, Richard Berendt, Naresh Jha and Mrinal Mandal. "Novel lymph node segmentation for skin cancer biopsy images". In Proceedings of BHI-2018 International Conference on Biomedical and Health Informatics (BHI), Mar 2018
  9. Hongming Xu, Richard Berendt, Naresh Jha and Mrinal Mandal. "Automated diagnosis of melanoma from skin biopsy images". In Proceedings of BHI-2017 International Conference on Biomedical and Health Informatics (BHI), Feb 2017
  10. Hongming Xu and Mrinal Mandal. "Robust segmentation of regions of interest in skin histopathological images". The 6th Annual Graduate Research Symposium, University of Alberta, June 2015 Oral Presentation
  11. Hongming Xu and Mrinal Mandal. "A novel technique for nuclei segmentation in skin histopathological images". The 5th Annual Graduate Research Symposium, University of Alberta, June 2014