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Publications from Laboratory of AI for Digital Health | Engineering Science Department | University of Oxford

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Publications

Latest Publications

Conference Papers
  1. Cai, Zi, et al. "ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions." Proceedings of the 34th ACM International Conference on Information and Knowledge Management. 2025. paper, code
  2. Yangyang, Xu, et al. "Cross-Subject Mind Decoding from Inaccurate Representations." Proceedings of the ieee/cvf international conference on computer vision. 2025. paper
  3. Liu, Yu, et al. "SurvUnc: A Meta-Model Based Uncertainty Quantification Framework for Survival Analysis." Proceedings of the 31th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. 2025. paper, code
  4. Li, Chenqi, et al. "AnchorInv: Few-Shot Class-Incremental Learning of Physiological Signals via Feature Space-Guided Inversion." Proceedings of the AAAI Conference on Artificial Intelligence. Vol. 39. No. 13. 2025. paper, code
  5. Luo, Zhiyao, et al. "Position: reinforcement learning in dynamic treatment regimes needs critical reexamination." Proceedings of the 41st International Conference on Machine Learning. 2024. paper, code
Journal Papers
  1. Yuan, Kevin, et al. "Transformers and large language models are efficient feature extractors for electronic health record studies." Communications Medicine 5.1 (2025): 83. paper, code
  2. Ghosheh, Ghadeer O., Moritz Gögl, and Tingting Zhu. "A perspective on individualized treatment effects estimation from time-series health data." Journal of the American Medical Informatics Association (2025): ocae323. paper
  3. Yuan, Kevin, et al. "Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections." Journal of Infection 90.2 (2025): 106388. paper
  4. Zhang, Shuo, et al. "Student loss: Towards the probability assumption in inaccurate supervision." IEEE Transactions on Pattern Analysis and Machine Intelligence 46.6 (2024): 4460-4475. paper, code
  5. Mesinovic, Munib, Peter Watkinson, and Tingting Zhu. "DySurv: dynamic deep learning model for survival analysis with conditional variational inference." Journal of the American Medical Informatics Association (2024): ocae271. paper
  6. Ghosheh, Ghadeer O., Jin Li, and Tingting Zhu. "A survey of generative adversarial networks for synthesizing structured electronic health records." ACM Computing Surveys 56.6 (2024): 1-34. paper
  7. Li, Chenqi, Timothy Denison, and Tingting Zhu. "A Survey of Few-Shot Learning for Biomedical Time Series." IEEE Reviews in Biomedical Engineering (2024). paper
Pre-Prints
  1. Mesinovic, Munib, et al. "Foundation model embeddings enable cardiovascular screening for people living with HIV in Vietnam using wearable signals." medRxiv (2025): 2025-10. paper
  2. Luo, Zhiyao, and Tingting Zhu. "Are Large Language Models Dynamic Treatment Planners? An In Silico Study from a Prior Knowledge Injection Angle." arXiv preprint arXiv:2508.04755 (2025). paper
  3. Li, Chenqi, et al. "BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals." arXiv preprint arXiv:2510.02276 (2025). paper
  4. Mingcheng, Zhu, et al. "Bridging Data Gaps of Rare Conditions in ICU: A Multi-Disease Adaptation Approach for Clinical Prediction." arXiv preprint arXiv:2507.06432 (2025). paper
  5. Liu, Yu, et al. "Identifying profiles, trajectories, burden, social and biological factors in 3.3 million individuals with multimorbidity in England." medRxiv (2025): 2025-05. paper
  6. Mesinovic, Munib, et al. "DynaGraph: Interpretable Multi-Label Prediction from EHRs via Dynamic Graph Learning and Contrastive Augmentation." arXiv preprint arXiv:2503.22257 (2025). paper, code
  7. Liu, Yu, et al. "Identifying profiles, trajectories, burden, social and biological factors in 3.3 million individuals with multimorbidity in England." medRxiv (2025): 2025-05. paper
  8. Mesinovic, Munib, et al. "DynaGraph: Interpretable Multi-Label Prediction from EHRs via Dynamic Graph Learning and Contrastive Augmentation." arXiv preprint arXiv:2503.22257 (2025). paper
  9. Ghosheh, Ghadeer O., Jin Li, and Tingting Zhu. "Understanding Missingness in Time-series Electronic Health Records for Individualized Representation." arXiv preprint arXiv:2402.15730 (2024). paper
  10. Luo, Zhiyao, et al. "DTR-bench: an in silico environment and benchmark platform for reinforcement learning based dynamic treatment regime." arXiv preprint arXiv:2405.18610 (2024). paper
  11. Ghosheh, Ghadeer O., Jin Li, and Tingting Zhu. "Understanding Missingness in Time-series Electronic Health Records for Individualised Representation." arXiv preprint arXiv:2402.15730 (2024). paper
  12. Ghosheh, Ghadeer O., Jin Li, and Tingting Zhu. "IGNITE: Individualized GeNeration of Imputations in Time-series Electronic health records." arXiv preprint arXiv:2401.04402 (2024). paper

All Publications

Explainability in the age of large language models for healthcare.

Mesinovic M, Watkinson P & Zhu T (2025), Commun Eng, 4(1), 128

Altmetric score is
BibTeX View PDF 
@article{explainabilityi-2025/7,
  title={Explainability in the age of large language models for healthcare.},
  author={Mesinovic M, Watkinson P & Zhu T},
  journal={Commun Eng},
  volume={4},
  pages={128},
  year = "2025"
}

Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data

Mesinovic M, Watkinson P & Zhu T (2025), Scientific Reports, 15(1)

Altmetric score is
BibTeX View PDF 
@article{explainablemach-2025/7,
  title={Explainable machine learning for predicting ICU mortality in myocardial infarction patients using pseudo-dynamic data},
  author={Mesinovic M, Watkinson P & Zhu T},
  journal={Scientific Reports},
  volume={15},
  number={27887},
  publisher={Nature Research},
  year = "2025"
}

Multi-teacher self-distillation based on adaptive weighting and activation pattern for enhancing lightweight arrhythmia recognition

Wang Z, Ma C, Zhang S, Zhao M, Liu Y et al. (2025), Information Fusion, 103178-103178

Altmetric score is
BibTeX View PDF 
@article{multiteachersel-2025/4,
  title={Multi-teacher self-distillation based on adaptive weighting and activation pattern for enhancing lightweight arrhythmia recognition},
  author={Wang Z, Ma C, Zhang S, Zhao M, Liu Y et al.},
  journal={Information Fusion},
  pages={103178-103178},
  publisher={Elsevier},
  year = "2025"
}

Transformers and large language models are efficient feature extractors for electronic health record studies

Yuan K, Yoon CH, Gu Q, Munby H, Walker AS et al. (2025), communications medicine, 5(1)

Altmetric score is
BibTeX View PDF 
@article{transformersand-2025/3,
  title={Transformers and large language models are efficient feature extractors for electronic health record studies},
  author={Yuan K, Yoon CH, Gu Q, Munby H, Walker AS et al.},
  journal={communications medicine},
  volume={5},
  number={83},
  publisher={Nature Research},
  year = "2025"
}

Uncertainty-Inspired Multi-Task Learning in Arbitrary Scenarios of ECG Monitoring.

Wang X, Gao H, Ma C, Zhu T, Yang F et al. (2025), IEEE journal of biomedical and health informatics, PP

Altmetric score is
BibTeX View PDF 
@article{uncertaintyinsp-2025/2,
  title={Uncertainty-Inspired Multi-Task Learning in Arbitrary Scenarios of ECG Monitoring.},
  author={Wang X, Gao H, Ma C, Zhu T, Yang F et al.},
  journal={IEEE journal of biomedical and health informatics},
  volume={PP},
  year = "2025"
}
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