Publications

Lewis Howell, Amir Zarei, Tze Min Wah, James H. Chandler, Shishir Karthik, Zara Court, Helen Ng & James R. McLaughlan. “RADEX: a rule-based clinical and radiology data extraction tool demonstrated on thyroid ultrasound reports” Springer Nature Link (2025). Link: https://link.springer.com/article/10.1007/s00330-025-11416-4

Breen J, Allen K, Zucker K, Godson L, Orsi NM, Ravikumar N. A comprehensive evaluation of histopathology foundation models for ovarian cancer subtype classification. NPJ Precision Oncology, (2025). Link: https://doi.org/10.1038/s41698-025-00799-8.

Andrew, D. R. Westhead, and L. Cutillo. "The Strong Product Model for Network Inference without Independence Assumptions" Proceedings of AISTATS 2025. Link: (TBC)

B. Andrew, D. R. Westhead, and L. Cutillo. "Graphical Modelling without Independence Assumptions for Uncentered Data" Proceedings of AAAI 2025. Link: (TBC)

Moglia, Victoria. O.A. Johnson, G. Cook, M. de Kamps & l.F. Smith. "Artificial intelligence methods applied to longitudinal data from electronic health records for prediction of cancer: a scoping review." BMC Medical Research Methodology 2025 Link: https://link.springer.com/article/10.1186/s12874-025-02473-w?utm

Zoe Hancox, Allan Pang, Philip G. Conaghan, Sarah R. Kingsbury, Andrew Clegg, Samuel D. Relton. “A systematic review of networks for prognosis prediction of health outcomes and diagnostic prediction of health conditions within Electronic Health Records.” Science Direct. Artificial Intelligence in Medicine. Vol 158. (2024) Link: https://www.sciencedirect.com/science/article/pii/S0933365724002410

Keel, Ben. Aaron Quyn, David Jayne, Samuel David Relton. State-of-the-art performance of deep learning methods for pre-emptive radiologic staging f colorectal cancer lymph node metastasis: a scoping view BMJ Open (2024) Link: https://bmjopen.bmj.com/content/14/12/e086896

Andrew, B., Zulcinski, M., Emmett, A., Westhead, D.R. (2024). Recent Developments in Transcriptomic Technologies: Applications to Immunological Systems and Diseases. In: Barciszewski, J. (eds) Systems Biology II. RNA Technologies, vol 15. Springer, Cham. https://doi.org/10.1007/978-3-031-62178-9_9

Ellis, Edward. Andrew Bulpitt, Sharib Ali. "Ultrasound Image Segmentation and its Evaluation using Various Encoder Architectures." IEEE Xplore (2024) Link: https://ieeexplore.ieee.org/abstract/document/10601122

Siân Carey, Allan Pang, Mark de Kamps. “Fairness in AI for healthcare.” Future Health Journal (2024) Link: https://doi.org/10.1016/j.fhj.2024.100177

Zoe Hancox, Sarah R. Kingsbury, Andrew Clegg, Philip G. Conaghan, Samuel D. Relton. “Developing the Temporal Graph Convolutional Neural Network Model to Predict Hip Replacement using Electronic Health Records” International Conference on Machine Learning and Applications (ICMLA). arXiv:2409.06585 (2024) Link: https://arxiv.org/abs/2409.06585

Wójcik, Zuzanna, MSc. Vania Dimitrova PhD, Lorraine Warrington PhD, Galina Velikova BMBS(MD), PhD, & Kate Absolom PhD. Patient-Centric Approach for Utilising Machine Learning to Predict Health-Related Quality of Life Changes During Chemotherapy. Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14844)) (2024) Link: https://link.springer.com/chapter/10.1007/978-3-031-66538-7_12

Wójcik, Zuzanna, MSc. Vania Dimitrova PhD, Lorraine Warrington PhD, Galina Velikova BMBS(MD), PhD, & Kate Absolom PhD. Using Machine Learning to Predict Unplanned Hospital Utilization and Chemotherapy Management From Patient-Reported Outcome Measures. JCO Clinical informatics. Vol 8. (2024) Link: https://doi.org/10.1200/CCI.23.00264

Andrew, Bailey E., D. R. Westhead, and L. Cutillo. "GmGM: a fast multi-axis Gaussian graphical model." In Proceedings of AISTATS 2024. Proceedings of Machine Learning Research, 2024.Link: https://proceedings.mlr.press/v238/b-andrew24a.html

Keel, Benjamin, Quyn, A., Jayne, D., Relton, S. D. (2023). Variational Autoencoders for Feature Exploration and Malignancy Prediction of Lung Lesions. British Machine Vision Conference 2023. Link: https://arxiv.org/abs/2311.15719

Godson, Lucy, et al. "Immune subtyping of melanoma whole slide images using multiple instance learning." Medical Image Analysis 93 (2024): 103097.

Coles, Alex D., C. D. McInerney, K. Zucker, S. Cheeseman, O. A. Johnson, and G. Hall. "Evaluation of machine learning methods for the retrospective detection of ovarian cancer recurrences from chemotherapy data." ESMO Real World Data and Digital Oncology 4 (2024): 100038.

Harkness, Rachael, et al. "Multi-centre benchmarking of deep learning models for COVID-19 detection in chest x-rays." Frontiers in radiology 4 (2024): 1386906.

Allen, Katie E., Pratik Adusumilli, Jack Breen, Geoffrey Hall, and Nicolas M. Orsi. "Artificial Intelligence in Ovarian Digital Pathology." In Pathology of the Ovary, Fallopian Tube and Peritoneum, pp. 731-749. Cham: Springer International Publishing, 2024.

Breen, Jack, et al. "Generative Adversarial Networks for Stain Normalisation in Histopathology." Applications of Generative AI. Cham: Springer International Publishing, 2024. 227-247.

B. Andrew, D. R. Westhead, and L. Cutillo. "GmGM: a fast multi-axis Gaussian graphical model." Proceedings of AISTATS 2024. Proceedings of Machine Learning Research, 2024.

Howell, Lewis, Nicola Ingram, Roger Lapham, Adam Morrell, and James R. McLaughlan. "Deep learning for real-time multi-class segmentation of artefacts in lung ultrasound." Ultrasonics (2024): 107251.

Loza, Gerardo, Pietro Valdastri, and Sharib Ali. "Real‐time surgical tool detection with multi‐scale positional encoding and contrastive learning." Healthcare Technology Letters 11.2-3 (2024): 48-58.

Freeston, Jane, Matthew Marzetti, Neal Larkman, Emma Rowbotham, Paul Emery, and Andrew Grainger. "Whole-body MRI for the investigation of joint involvement in inflammatory arthritis." Skeletal Radiology 53, no. 5 (2024): 935-945.

Godson, Lucy, Navid Alemi, Jérémie Nsengimana, Graham P. Cook, Emily L. Clarke, Darren Treanor, D. Timothy Bishop, Julia Newton-Bishop, and Derek Magee. "Multi-level Graph Representations of Melanoma Whole Slide Images for Identifying Immune Subgroups." In International Conference on Medical Image Computing and Computer-Assisted Intervention, pp. 85-96. Cham: Springer Nature Switzerland, 2023.

Harkness, R., Frangi, A. F., Zucker, K., & Ravikumar, N. 2023. Learning disentangled representations for explainable chest x-ray classification using Dirichlet VAEs, Proc. SPIE 12464, Medical Imaging 2023: Image Processing, 1246411 (3 April 2023).

Keighley, Jason, Marc de Kamps, Alexander Wright, and Darren Treanor. "Digital pathology whole slide image compression with vector quantized variational autoencoders." In Medical Imaging 2023: Digital and Computational Pathology, vol. 12471, pp. 344-353. SPIE, 2023.

Allen, K., J. Breen, K. Zucker, N. Ravikumar, G. Hall, and N. Orsi. "Can AI replace the Gynaecological Pathologist in Reporting Tumours of the Ovary, Fallopian Tube and Peritoneum? A Proposed Roadmap." In JOURNAL OF PATHOLOGY, vol. 261, no. SUPPL 1, pp. S36-S36. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2023.

Allen, K., A. Bano, J. Breen, K. Zucker, N. Ravikumar, G. Hall, and N. Orsi. "Creation of a World-Leading Digital Pathology Dataset of Tubo-ovarian and Peritoneal Carcinomas for Development of Artificial Intelligence Models." In JOURNAL OF PATHOLOGY, vol. 261, no. SUPPL 1, pp. S36-S36. 111 RIVER ST, HOBOKEN 07030-5774, NJ USA: WILEY, 2023.

Allen, Katie E., Jack Breen, Geoff Hall, Kieran Zucker, Nishant Ravikumar, and Nicolas M. Orsi. "# 900 Comparative evaluation of ovarian carcinoma subtyping in primary versus interval debulking surgery specimen whole slide images using artificial intelligence." (2023).

Breen, J., Allen, K., Zucker, K., Hall, G., Orsi, N. M., & Ravikumar, N. 2023. Efficient subtyping of ovarian cancer histopathology whole slide images using active sampling in multiple instance learning. In Medical Imaging 2023: Digital and Computational Pathology (Vol. 12471, pp. 248-258). SPIE.

Breen, Jack, Katie Allen, Kieran Zucker, Pratik Adusumilli, Andrew Scarsbrook, Geoff Hall, Nicolas M. Orsi, and Nishant Ravikumar. "Artificial intelligence in ovarian cancer histopathology: a systematic review." NPJ Precision Oncology 7, no. 1 (2023): 83.

Hancox, Zoe, Samuel D. Relton, Andrew Clegg, Philip G. Conaghan, and Dan Schofield. "Hypergraphs for Frailty Analysis Research Paper." In International Conference on Process Mining, pp. 271-282. Cham: Springer Nature Switzerland, 2023.

Paterson, Mary, James Moor, and Luisa Cutillo. "A Pipeline to Evaluate the Effects of Noise on Machine Learning Detection of Laryngeal Cancer." Proceedings of Interspeech 2023. International Speech Communication Association, 2023.

Keel, Benjamin, Aaron Quyn, David Jayne, and Samuel D. Relton. "Variational Autoencoders for Feature Exploration and Malignancy Prediction of Lung Lesions." (2023).

Anna-Grace Linton, Vania Dimitrova, Amy Downing, Richard Wagland, Adam Glaser. Automated Thematic Classification of Patient-Reported Outcome Free Text Comments Using Weakly Supervised Text Classification. Conference: 7th UK Patient Reported Outcome Measures (PROMs) Research Conference: 'PROMs Across the Lifespan'. Sheffield, UK. 2023.

Zuzanna Wojcik, Vania Dimitrova, Kate Absolom, Lorraine Warrington, Galina Velikova. Predicting Hospital Utilisation and Chemotherapy Management from Patient-Reported Outcome Measures Collected in a Clinical Trial. 7th UK Patient Reported Outcome Measures (PROMs) Research Conference: 'PROMs Across the Lifespan'. Sheffield, UK. 2023

A, G. Linton, V. Dimitrova, A. Downing, R. Wagland, A. Glase. 2023. Weakly Supervised Classification of PROMs Free Text Comments. Healthcare Text Analytics conference 2023.

Broad, Andrew, Alexander I. Wright, Marc de Kamps, and Darren Treanor. "Attention-guided sampling for colorectal cancer analysis with digital pathology." Journal of Pathology Informatics 13 (2022): 100110.

Sims, Joe, Heike I. Grabsch, and Derek Magee. "Using Hierarchically Connected Nodes and Multiple GNN Message Passing Steps to Increase the Contextual Information in Cell-Graph Classification." MICCAI Workshop on Imaging Systems for GI Endoscopy. Cham: Springer Nature Switzerland, 2022.

Briggs, E., de Kamps, M., Hamilton, W., Johnson, O., McInerney, C.D., Neal, R.D. 2022. Machine Learning for Risk Prediction of Oesophago-Gastric Cancer in Primary Care: Comparison with Existing Risk-Assessment Tools. Cancers. 14(20), pp. 5023-5023.

Hancox, Zoe, and Samuel D. Relton. "Temporal graph-based CNNs (TG-CNNs) for online course dropout prediction." International Symposium on Methodologies for Intelligent Systems. Cham: Springer International Publishing, 2022.

Bullward, A., Aljebreen, A., Coles, A., McInerney, C.D., Johnson, O. Process Mining and Synthetic Health Data: Reflections and Lessons Learnt. Best paper at the 5th International Workshop on Process-Oriented Data Science for Healthcare (PODS4H22).

Paterson, M., Moor, J., Cutillo, L. 2022. Investigating the Effects of Environmental Factors on the Detection of Laryngeal Cancer from Speech Signals Using Machine Learning. Conference on Neural Information Processing Systems (NeurIPS). New Orléans.

Andrew, B., Westhead D., Cutillo, L. 2022. antGLasso: An Efficient Tensor Graphical Lasso Algorithm. Conference on Neural Information Processing Systems (NeurIPS). New Orléans.

Wilson, B. I., Magee, D. R., Grabsch, H. I., West, N. P., Quirke, P. 2022. Towards Automated Quantification of the Tumour Microenvironment using Fully Convolutional Neural Networks. In Journal Of Pathology (Vol. 256, Pp. S13-S13). 111 River St, Hoboken 07030-5774, NJ, USA, Wiley.

Sims, J., Grabsch, H.I., Magee, D. 2022. Using Hierarchically Connected Nodes and Multiple GNN Message Passing Steps to Increase the Contextual Information in Cell-Graph Classification. In:, et al. Imaging Systems for GI Endoscopy, and Graphs in Biomedical Image Analysis. ISGIE GRAIL 2022. Lecture Notes in Computer Science, vol 13754. Springer, Cham.

Godson, L., Alemi, N., Nsengimana, J., Cook, G.P., Clarke, E.L., Treanor, D., Bishop, D.T., Newton-Bishop, J. and Gooya, A. 2022. Weakly-supervised learning for image-based classification of primary melanomas into genomic immune subgroups. Proceedings of The 5th International Conference on Medical Imaging with Deep Learning, PMLR 172:423-440

Harkness, Rachael, et al. "The pitfalls of using open data to develop deep learning solutions for COVID-19 detection in chest X-rays." MEDINFO 2021: One World, One Health–Global Partnership for Digital Innovation. IOS Press, 2022. 679-683.

Breen, J., Zucker, K., Orsi, N.M., Ravikumar, N. 2022. Assessing Domain Adaptation Techniques for Mitosis Detection in Multi-scanner Breast Cancer Histopathology Images. In: Biomedical Image Registration, Domain Generalisation and Out-of-Distribution Analysis. MICCAI 2021. Lecture Notes in Computer Science, vol 13166. Springer, Cham.

Shang, Z. Zhao, H.Fang, S. Relton, D. Murphy, Z. Hancox, R.Yan, D. Wong. Deep Discriminative Domain Generalization with Adversarial Feature Learning for Classifying ECG Signals. 2021 Computing in Cardiology (CinC), Brno, Czech Republic, 2021, pp. 1-4, DOI