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Publications from the Turing AI Fellowship programme at the University of Oxford

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Publications

  •  J Strong, H Rogers, E Sun, AS Todsen, J Ede, C Lumley, N Yeung, H Higham, JA Noble, Human-AI Collaboration in Healthcare: A Scoping Review, npj Digital Medicine 2026.

  • J Strong, P Saha, Y Ibrahim, C Ouyang, A Noble, Identity-Free Deferral for Unseen Experts, ICLR 2026.

  • H Lamdouar, AF Wang, X Guo, Q Men, J Lander, AT Papageorghiou, JA Noble, FOCUS: Towards Fetal Obstetric Corrective Ultrasound Guidance, MICCAI 2026.

  • A. Le et al, US-Bench: benchmarking large vision-language models for ultrasound understanding, ICLR26.

  • Liang Z, Guo X, Xu W, Ibrahim Y, Voets N, Pretorius PM; Alzheimer’s Disease Neuroimaging Initiative; Noble JA, Kamnitsas K. IterMask3D: Unsupervised anomaly detection and segmentation with test-time iterative mask refinement in 3D brain MRI. Med Image Anal. 2026 Jan;107(Pt A):103763. doi: 10.1016/j.media.2025.103763. Epub 2025 Aug 28. PMID: 40945172.

  • C Peng, Exploring Neural Collapse in multi-label skewed federated learning, ECCV 2026.

  • A Le, C Peng, Y Liu and JA Noble, POUR: A Provable Optimal Method for Unlearning Representations via Neural Collapse, CVPR 2026.

  • A Le, C Peng, H Guo, JA Noble, DECAF: Declustering for Adaptive Representational Unlearning, ICML 2026 Continual Adaptation at Scale: Towards Sustainable AI Workshop.

  • Pramit Saha, Divyanshu Mishra, Felix Wagner, Konstantinos Kamnitsas, J. Alison Noble, FedExIT - missing class-agnostic semi-supervised federated learning with extreme imbalance tackling scheme Information Fusion, Volume 130, June 2026, 104080 https://doi.org/10.1016/j.inffus.2025.104080

  • J Strong, Q Men, JA Noble, Trustworthy and Practical AI for Healthcare: A guided deferral system with Large Language Models, The 39th AAAI Conference on Artificial Intelligence (AAAI-25), 2025.

  • X Guo, M Alsharid, H Zhao, Y Wang, J Lander, AT Papageorghiou, JA Noble, Sonomate: Visually grounded language model for fetal ultrasound understanding and human interaction, Nature Biomedical Engineering, accepted July 2025.

  • Qianhui Men, He Zhao, Lior Drukker, Aris T. Papageorghiou, J. Alison Noble, ScanAhead: Simplifying standard plane acquisition of fetal head ultrasound, Medical Image Analysis, Volume 104, 2025, 103614, ISSN 1361-8415, https://doi.org/10.1016/j.media.2025.103614

  •  M AlSharid, X Gui, Q Men P Saha, D Mishra, R Ahuja, C Ouyang, JA Noble, On the public dissemination and open sourcing of ultrasound resources, datasets and deep learning models, npj Digital Medicine, 2025.

  • A Nicolson, E Bradburn, Y Gal, AS Papageorghiou, JA Noble, The Human Factor in explainable artificial intelligence: clinician variability in trust, reliance and performance, npj Digital Medicine (accepted 2025).

  • Jiazhen Pan, Che Liu, Junde Wu, Fenglin Liu, Jiayuan Zhu, Hongwei Bran Li, Chen Chen, Cheng Ouyang, Daniel Rueckert, MedVLM-R1: Incentivizing Medical Reasoning Capability of Vision-Language Models (VLMs) via Reinforcement Learning. In: Gee, J.C., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2025. MICCAI 2025. Lecture Notes in Computer Science, vol 15966. Springer, Cham. https://doi.org/10.1007/978-3-032-04981-0_32

  • J Zhu, J Wu, C Ouyang, L Kamnitsas, JA Noble, SPA: Efficient User-Preference Alignment against Uncertainty in Medical Image Segmentation, ICCV25

  • P Saha, D Mishra, N Hernandez-Cruz, O Patey, AT. Papageorghiou, YM. Asano, and JA Noble. 2025. Self-supervised Normality Learning and Divergence Vector-Guided Model Merging for Zero-Shot Congenital Heart Disease Detection in Fetal Ultrasound Videos. In Medical Image Computing and Computer Assisted Intervention – MICCAI 2025: 28th International Conference, Daejeon, South Korea, September 23–27, 2025, Proceedings, Part VII. Springer-Verlag, Berlin, Heidelberg, 560–571. https://doi.org/10.1007/978-3-032-04981-0_53

  • P Saha, D, Mishra, F Wagner, K Kamnitsas, JA Noble, FedPIA - Permuting and Integrating Adapters Leveraging Wasserstein Barycenters for Finetuning Foundation Models in Multi-Modal Federated Learning, AAAI-2025, https://doi.org/10.1609/aaai.v39i19.34228

  • F Wagner, P Saha, H Anthony. JA Noble, K Kamnitsas, DIsoN: Decentralized Isolation Networks for Out-of-Distribution Detection in Medical Imaging, NeurIPS 2025

  • Saha, P., Mishra, D., Wagner, F., Kamnitsas, K., & Noble, J. A. (2025). Incongruent Multimodal Federated Learning for Medical Vision and Language-based Multi-label Disease Detection. Proceedings of the AAAI Conference on Artificial Intelligence, 39(27), 28331-28339. https://doi.org/10.1609/aaai.v39i27.35054

  • F. Wagner, W Xu, P Saha, Z Liang, D Whitehouse, D Menon, V Newcombe, N Voets, JA Noble, K Kamnitsas, "Feasibility of Federated Learning from Client Databases with Different Brain Diseases and MRI Modalities," 2025 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV), Tucson, AZ, USA, 2025, pp. 357-367, doi: 10.1109/WACV61041.2025.00045.

  • Pramit Saha, Felix Wagner, Divyanshu Mishra, Can Peng, Anshul Thakur, David Clifton, Konstantinos Kamnitsas, J. Alison Noble, "F3OCUS - Federated Finetuning of Vision-Language Foundation Models with Optimal Client Layer Updating Strategy via Multi-objective Meta-Heuristics," 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), Nashville, TN, USA, 2025, pp. 20006-20017, doi: 10.1109/CVPR52734.2025.01863.

  •  J Strong, Q Men, A Noble, Towards Human-AI Collaboration in Healthcare: Guided Deferral Systems with Large Language Models. ICML 2024 Workshop on LLMs and Cognition.  https://openreview.net/forum?id=4c5rg9y4me

  • Hernandez-Cruz N, Saha P, Sarker MMK, Noble JA. Review of Federated Learning and Machine Learning-Based Methods for Medical Image Analysis. Big Data and Cognitive Computing. 2024; 8(9):99. https://doi.org/10.3390/bdcc8090099

  •  X Guo, Q Men, JA Noble, (2024). MMSummary: Multimodal Summary Generation for Fetal Ultrasound Video. In: Linguraru, M.G., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2024. MICCAI 2024. Lecture Notes in Computer Science, vol 15004. Springer, Cham. https://doi.org/10.1007/978-3-031-72083-3_63 

  • Men, Qianhui and Guo, Xianoqing and Papagerghiou, Aris T. and Noble, J. Alison, Pose-GuidedNet: Automatic Scanning Guidance for Fetal Head Ultrasound from Pose Etimation, MICCAI 2024, pages 700-710 https://doi.org/10.1007/978-3-031-72083-3_65

  • A Nicolson, Y Gal. A Noble, TextCAVs: Debugging vision models using text, iMIMIC24 (MICCAI Workshop), 2024.

  • Liang, Z., Guo, X., Noble, J. A., & Kamnitsas, K. (2024, October). Itermask 2: Iterative unsupervised anomaly segmentation via spatial and frequency masking for brain lesions in mri. In International Conference on Medical Image Computing and Computer-Assisted Intervention (pp. 339-348). Cham: Springer Nature Switzerland.

  • Saha, P., Mishra, D., Noble, J.A. (2023). Rethinking Semi-Supervised Federated Learning: How to Co-train Fully-Labeled and Fully-Unlabeled Client Imaging Data. In: Greenspan, H., et al. Medical Image Computing and Computer Assisted Intervention – MICCAI 2023. MICCAI 2023. Lecture Notes in Computer Science, vol 14221. Springer, Cham. https://doi.org/10.1007/978-3-031-43895-0_39