Medical Image Analysis

• Zhu, M., Liu, M., Yuan, H., … & Liu, N. (2026). Attention Guided Fair Artificial Intelligence Modeling for Skin Cancer Diagnosis. Nature Partner Journal Digital Medicine. (Paper, Code)
• Yuan, H., … & Hong, C. (2025). Rethinking Domain-specific Pre-training by Supervised or Self-supervised Learning for Chest Radiograph Classification: A Comparative Study against ImageNet Counterparts in Cold-start Active Learning. Health Care Science. (Paper, Code)
• Yuan, H., Kang, L. & Li, Y. (2025). Opening the Black Box of Deep Learning: Validating the Statistical Association between Explainable Artificial Intelligence and Clinical Domain Knowledge in Fundus Image-based Glaucoma Diagnosis. arXiv. (Paper, Code)
• Yuan, H., Hong, C., … & Liu, N. (2024). Clinical Domain Knowledge-derived Template Improves Post Hoc AI Explanations in Pneumothorax Classification. Journal of Biomedical Informatics. (Paper, Code)
• Yuan, H., Hong, C., … & Liu, N. (2024). Leveraging Anatomical Constraints with Uncertainty for Pneumothorax Segmentation. Health Care Science. (Paper, Code, Poster)
• Yuan, H. (2024). Anatomic Boundary-aware Explanation for Convolutional Neural Networks in Diagnostic Radiology. iRadiology. (Paper, Code)
• Yuan, H. & Hong, C. (2024). Foundation Model Makes Clustering A Better Initialization For Cold-Start Active Learning. arXiv. (Paper, Code)
• Zhu, M., Liu, M., Yuan, H., … & Liu, N. (2024). Clinical Knowledge-integrated AI Towards Gender Fairness in Skin Cancer Diagnosis. arXiv. (Paper, Code)
• Yuan, H., Jiang, P. & Zhao, G. (2023). Human-Guided Design to Explain Deep Learning-based Pneumothorax Classifier. Medical Imaging with Deep Learning, Short Paper Track. (Paper, Code, Poster)

Natural Language Processing

• Yuan, H., Zhao, Y., Zhang, L., Luo, W. & Ma, Z. (2026). Quantifying the Impact of Structured Output Format on Large Language Models through Causal Inference. Findings of the Association for Computational Linguistics: EACL 2026, Long Paper Track. (Paper, Code, Poster)
• Yuan, H., Wu, Y., Zhang, L. & Ma, Z. (2026). Empowering Small Language Models with Factual Hallucination-Aware Reasoning for Financial Classification. AAAI Workshop on Trust and Control in Agentic AI, Long Paper Track. (Paper, Code, Poster)
• Zhao, Y., Pandelea, V., Yuan, H.☯︎, Hu, B., Luo, W., Zhang, L. & Ma, Z. (2026). A Citation-Grounded Benchmark for Trustworthy Earnings Call Transcript Analysis with Large Language Models. NeurIPS Workshop on Attributing Model Behavior at Scale: Data Attribution and Provenance, Long Paper Track. (Paper, Code, Poster)
• Liu, M., Yuan, H., Wu, Y., Zhang, L., & Ma, Z. (2026). Semi-Supervised Learning to Improve Detection of Factual and Causal Errors in Language Models’ Explanations. The EMNLP Workshop on Grounding Language Models Learning Faithfully and Efficiently, Short Paper Track. (Paper, Code, Poster)
• Yuan, H., Zhang, L. & Ma, Z. (2025). Exploring the Reliability of Self-explanation and its Relationship with Classification in Language Model-driven Financial Analysis. ICLR Workshop on Advances in Financial AI, Short Paper Track. (Paper, Code, Poster)
• Wu, Y., Yuan, H.☯︎, Zhang, L., & Ma, Z. (2025). Natural Language Inference as a Judge: Detecting Factuality and Causality Issues in Language Model Self-Reasoning for Financial Analysis. EMNLP Workshop on Financial Technology and Natural Language Processing, Long Paper Track. (Paper, Code, Poster)
• Hu, B., Yuan, H.☯︎, Pandelea, V., Luo, W., Zhao, Y. & Ma, Z. (2025). Extract, Match, and Score: An Evaluation Paradigm for Long Question-context-answer Triplets in Financial Analysis. ICLR Workshop on Advances in Financial AI, Long Paper Track. (Paper, Poster)
• Chen, Y., … Yuan, H., … & Li, I. (2025). GraphCheck: Breaking Long-Term Text Barriers with Extracted Knowledge Graph-Powered Fact-Checking. The Annual Meeting of the Association for Computational Linguistics, Long Paper Track. (Paper, Code)
• Li, F., … Yuan, H., … & Li, I. (2025). MKG-Rank: Enhancing Large Language Models with Knowledge Graph for Multilingual Medical Question Answering. (Paper, Code)
• Yuan, H. (2025). Agentic Large Language Models for Healthcare: Current Progress and Future Opportunities. Medicine Advances. (Paper)
• Yuan, H. (2025). Toward Comprehensive Evaluation of Medical Text Generation by Large Language Models (LLMs): Programmatic Metrics, Human Assessment, and LLMs Judgment. Medicine Advances. (Paper)
• Yuan, H. (2025). Natural Language Processing for Chest X-ray Report in the Transformer Era: BERT-like Encoder for Comprehension and GPT-like Decoder for Generation. iRadiology. (Paper)
• Zhao, Y., Yuan, H.☯︎ & Wu, Y. (2021). Prediction of Adverse Drug Reaction using Machine Learning Based on an Imbalanced Electronic Medical Records Dataset. International Conference on Medical and Health Informatics, Full Paper Track. (Paper)

Multi-modality

• Li, Y., … Yuan, H., … & Ang, M. (2024). Effect of Childhood Atropine Treatment on Adult Choroidal Thickness Using Sequential Deep Learning-Enabled Segmentation. Asia-Pacific Journal of Ophthalmology. (Paper)
• Li, Y., … Yuan, H., … & Ang, M. (2024). Deep Learning Algorithms to Predict Response and Effect on Adult High Myopia in the Atropine Treatment Long-term Assessment Study. In Preparation. (Paper)
• Yuan, H., Yu, K., Xie, F., … & Sun, S. (2024). Automated Machine Learning with Interpretation: A Systematic Review of Methodologies and Applications in Healthcare. Medicine Advances. (Paper)

Reinforcement Learning

• Kang, L., … Yuan, H. & Zhu, C. (2024). Approximate Policy Iteration with Deep Minimax Average Bellman Error Minimization. IEEE Transactions on Neural Networks and Learning Systems. (Paper)
• Kang, L., Yuan, H. & Zhu C. (2023). Error Analysis of Fitted Q-iteration with ReLU-activated Deep Neural Networks. International Conference on Learning Representations, Tiny Paper Track. (Paper)

Structured Learning

• Yuan, H. (2025). Overcoming Computational Resource Limitations in Deep Learning for Healthcare: Strategies Targeting Data, Model, and Computing. Medicine Advances. (Paper)
• Yuan, H. (2024). Toward Real-world Deployment of Machine Learning for Healthcare: External Validation, Continual Monitoring, and Randomized Clinical Trials. Health Care Science. (Paper)
• Yuan, H. (2024). Clinical Decision Making: Evolving from Hypothetico-deductive Model to Knowledge-enhanced Machine Learning. Medicine Advances. (Paper)
• Yuan, H., … & Fan, Z. (2024). Human-in-the-loop Machine Learning for Healthcare: Current Progress and Future Opportunities in Electronic Health Records. Medicine Advances. (Paper)
• Liu, P., Yuan, H., … & Peres, M. (2024). A Modified Gower Distance-based Clustering Analysis for Mixed-type Data. BMC Medical Research Methodology. (Paper, Code)
• Yuan, H., Liu, M., … & Wu, Y. (2023). An empirical study of the effect of background data size on the stability of SHapley Additive exPlanations for deep learning models. International Conference on Learning Representations, Tiny Paper Track. (Paper, Code)
• Yuan, H., … & Xie, F. (2023). Interpretable Machine Learning-Based Risk Scoring with Individual and Ensemble Model Selection for Clinical Decision Making. International Conference on Learning Representations, Tiny Paper Track. (Paper, Code)
• Liu, M., Li, S., Yuan, H., … & Liu, N. (2023). Handling missing values in healthcare data: A systematic review of deep learning-based imputation techniques. Artificial Intelligence in Medicine. (Paper)
• Li, S., … Yuan, H., … & Liu, N. (2023). FedScore: A privacy-preserving framework for federated scoring system development. Journal of Biomedical Informatics. (Paper, Code)
• Xie, F., … Yuan, H., … & Liu, N. (2023). A universal AutoScore framework to develop interpretable scoring systems for predicting common types of clinical outcomes. STAR Protocols. (Paper, Code)
• Yuan, H., … & Liu, N. (2022). AutoScore-Imbalance: An interpretable machine learning tool for development of clinical scores with rare events data. Journal of Biomedical Informatics. (Paper, Code)
• Xie, F., Yuan, H.☯︎, … & Liu, N. (2022). Deep learning for temporal data representation in electronic health records: A systematic review of challenges and methodologies. Journal of Biomedical Informatics. (Paper)
• Xie, F., Ning, Y., Yuan, H., … & Chakraborty, B. (2022). AutoScore-Survival: Developing interpretable machine learning-based time-to-event scores with right-censored survival data. Journal of Biomedical Informatics. (Paper, Code)
• Liu, M., Ning Y., Yuan, H., … & Liu, N. (2022). Balanced background and explanation data are needed in explaining deep learning models with SHAP: An empirical study on clinical decision making. arXiv. (Paper)
• Miao, C., … Yuan, H., … & Wang, Z. (2021). TRIM37 orchestrates renal cell carcinoma progression via histone H2A ubiquitination-dependent manner. Journal of Experimental & Clinical Cancer Research. (Paper)
• Xie, F., Ning Y., Yuan, H., … & Liu, N. (2021). Package ‘AutoScore’: An Interpretable Machine Learning-Based Automatic Clinical Score Generator. R Package. (Paper, Code)
• Miao, C., Yu, A., Yuan, H.☯︎, … & Wang, Z. (2020). Effect of Enhanced Recovery After Surgery on Postoperative Recovery and Quality of Life in Patients Undergoing Laparoscopic Partial Nephrectomy. Frontiers in Oncology. (Paper)
• Zhang, J., Sun, Z., Yuan, H. & Wang, M. (2020). Alternatives to the Kaplan-Meier estimator of progression-free survival. The International Journal of Biostatistics. (Paper)

☯︎ Equal Contribution