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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. Gögl, Moritz, et al. "DoseSurv: Predicting Personalized Survival Outcomes under Continuous-Valued Treatments." The Thirty-ninth Annual Conference on Neural Information Processing Systems. paper, code
  2. 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
  3. Yangyang, Xu, et al. "Cross-Subject Mind Decoding from Inaccurate Representations." Proceedings of the ieee/cvf international conference on computer vision. 2025. paper
  4. 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
  5. 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
  6. 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. Mesinovic, Munib, et al. "DynaGraph: interpretable dynamic graph learning for temporal electronic health records." npj Digital Medicine (2026). paper, code
  2. Zhu, Mingcheng, et al. "Bridging data gaps of rare conditions in ICU: a multi-disease adaptation approach for clinical prediction." npj Digital Medicine (2026). paper, code
  3. Mesinovic, Munib, et al. "Foundation models enable wearable signal screening for cardiovascular disease among people living with HIV." Communications Medicine (2026). paper
  4. Mesinovic, Munib, Peter Watkinson, and Tingting Zhu. "Explainability in the age of large language models for healthcare." Communications Engineering 4.1 (2025): 128. paper 
  5. 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
  6. 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
  7. Yuan, Kevin, et al. "Machine learning and clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections." Journal of Infection 90.2 (2025): 106388. paper
  8. 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
  9. 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
  10. 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
  11. 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. 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
  2. Li, Chenqi, et al. "BioX-Bridge: Model Bridging for Unsupervised Cross-Modal Knowledge Transfer across Biosignals." arXiv preprint arXiv:2510.02276 (2025). paper
  3. 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
  4. 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
  5. 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
  6. 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
  7. 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
  8. 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
  9. 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

Bridging data gaps of rare conditions in ICU: a multi-disease adaptation approach for clinical prediction

Zhu M, Liu Y, Luo Z & Zhu T (2026), npj Digital Medicine, 9(1)

Altmetric score is
BibTeX View PDF 
@article{bridgingdatagap-2026/1,
  title={Bridging data gaps of rare conditions in ICU: a multi-disease adaptation approach for clinical prediction},
  author={Zhu M, Liu Y, Luo Z & Zhu T},
  journal={npj Digital Medicine},
  volume={9},
  number={7},
  publisher={Nature Research},
  year = "2026"
}

Foundation models enable wearable signal screening for cardiovascular disease among people living with HIV.

Mesinovic M, Bich HH, Trieu LV, Quoc VN, Thanh NN et al. (2026), Communications medicine

Altmetric score is
BibTeX View PDF 
@article{foundationmodel-2026/1,
  title={Foundation models enable wearable signal screening for cardiovascular disease among people living with HIV.},
  author={Mesinovic M, Bich HH, Trieu LV, Quoc VN, Thanh NN et al.},
  journal={Communications medicine},
  year = "2026"
}

ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions

Cai Z, Liu Y, Luo Z & Zhu T (2025), Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 169-178

Altmetric score is
BibTeX View PDF 
@inproceedings{protoehrhierarc-2025/11,
  title={ProtoEHR: Hierarchical Prototype Learning for EHR-based Healthcare Predictions},
  author={Cai Z, Liu Y, Luo Z & Zhu T},
  booktitle={CIKM '25: The 34th ACM International Conference on Information and Knowledge Management},
  pages={169-178},
  year = "2025"
}

Real-World Classification of Student Stress and Fatigue Using Wearable PPG Recordings

Laiti J, Liu Y, Dunne PJ, Byrne E & Zhu T (2025), IEEE Transactions on Affective Computing, PP(99), 1-16

Altmetric score is
BibTeX View PDF 
@article{realworldclassi-2025/11,
  title={Real-World Classification of Student Stress and Fatigue Using Wearable PPG Recordings},
  author={Laiti J, Liu Y, Dunne PJ, Byrne E & Zhu T},
  journal={IEEE Transactions on Affective Computing},
  volume={PP},
  pages={1-16},
  publisher={Institute of Electrical and Electronics Engineers (IEEE)},
  year = "2025"
}

Towards deployment-centric multimodal AI beyond vision and language

Liu X, Zhang J, Zhou S, van der Plas TL, Vijayaraghavan A et al. (2025), Nature Machine Intelligence, 7(10), 1612-1624

Altmetric score is
BibTeX View PDF 
@article{towardsdeployme-2025/10,
  title={Towards deployment-centric multimodal AI beyond vision and language},
  author={Liu X, Zhang J, Zhou S, van der Plas TL, Vijayaraghavan A et al.},
  journal={Nature Machine Intelligence},
  volume={7},
  pages={1612-1624},
  publisher={Springer Nature},
  year = "2025"
}
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