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Dr. Lin is an assistant professor in the Division of Computational Health Science and possesses extensive experience in medical image analysis. He has developed advanced techniques for medical image analysis, including segmentation, diagnosis, prognosis, and biomarker identification.
PhD, City University of Hong Kong, 2020
1. A Multimodal Approach for Few-Shot Biomedical Named Entity Recognition in Low-Resource Languages
(Journal: Journal of Biomedical Informatics), 2025
Authors: Jian Chen, Leilei Su, Yihong Li, Mingquan Lin, Yifan Peng, Cong Sun
2. Improving Fairness of Automated Chest Radiograph Diagnosis by Contrastive Learning
(Journal: Radiology: Artificial Intelligence), 2024
Authors: Mingquan Lin, Tianhao Li, Zhaoyi Sun, Gregory Holste, Ying Ding, Fei Wang, George Shih, Yifan Peng
3. Harnessing the Power of Longitudinal Medical Imaging for Eye Disease Prognosis Using Transformer-Based Sequence Modeling
(Journal: npj Digital Medicine), 2024
Authors: Gregory Holste, Mingquan Lin, Ruiwen Zhou, Fei Wang, Lei Liu, Qi Yan, Sarah H. Van Tassel, Kyle Kovacs, Emily Y. Chew, Zhiyong Lu, Zhangyang Wang, Yifan Peng
4. Deep Learning with Noisy Labels in Medical Prediction Problems: A Scoping Review
(Journal: Journal of the American Medical Informatics Association), 2024
Authors: Yishu Wei, Yu Deng, Cong Sun, Mingquan Lin, Hongmei Jiang, Yifan Peng
5. A New Classification Method for Diagnosing COVID-19 Pneumonia via Joint Parallel Deformable MLP Modules and Bi-LSTM With Multi-Source Generated Data of CXR Images
(Journal: IEEE Transactions on Consumer Electronics), 2024
Authors: Yiwen Liu, Wenyu Xing, Mingquan Lin, Yuping Liu, Tommy W.S. Chow
6. Explainable differential diagnosis with dual-inference large language models
(Journal: npj Health Systems), 2025
Authors: Shuang Zhou, Mingquan Lin, Sirui Ding, Jiashuo Wang, Canyu Chen, Genevieve B Melton, James Zou, Rui Zhang
7. Large Language Models for Disease Diagnosis: A Scoping Review
(Journal: npj Artificial Intelligence), 2025
Authors: Shuang Zhou, Zidu Xu, Mian Zhang, Chunpu Xu, Yawen Guo, Zaifu Zhan, Sirui Ding, Jiashuo Wang, Kaishuai Xu, Yi Fang, Liqiao Xia, Jeremy Yeung, Daochen Zha, Genevieve B Melton, Mingquan Lin, Rui Zhang
8. An empirical study of using radiology reports and images to improve intensive care unit mortality prediction
(Journal: JAMIA open), 2025
Authors: Mingquan Lin, Song Wang, Ying Ding, Lihui Zhao, Fei Wang, Yifan Peng
9. Towards Collaborative Fairness in Federated Learning Under Imbalanced Covariate Shift.
(Conference: KDD 2025), 2025
Authors: Tianrun Yu, Jiaqi Wang, Haoyu Wang, MINGQUAN LIN, Han Liu, Nelson S. Yee, Fenglong Ma
10. Seeing Far and Clearly: Mitigating Hallucinations in MLLMs with Attention Causal Decoding
(Conference: CVPR 2025), 2025
Authors: Feilong Tang, Chengzhi Liu, Zhongxing Xu, Ming Hu, Zile Huang, Haochen Xue, Ziyang Chen, Zelin Peng, Zhiwei Yang, Sijin Zhou, Wenxue Li, Yulong Li, Wenxuan Song, Shiyan Su, Wei Feng, Jionglong Su, MINGQUAN LIN, Yifan Peng, Xuelian Cheng, Imran Razzak, Zongyuan Ge
Dr. Lin's main research focus is on artificial intelligence in medical image analysis, encompassing segmentation, diagnosis, prognosis, and biomarker identification. Additionally, he is interested in multimodal biomedical studies that utilize text, images, clinical variables, and gene data for various tasks. He aims to develop advanced models that prioritize fairness, robustness, and explainability to enhance patient outcomes.