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Paterson, M., Moor, J., Cutillo, L. (2023) A Pipeline to Evaluate the Effects of Noise on Machine Learning Detection of Laryngeal Cancer. Proc. INTERSPEECH 2023, 2993-2997, doi: 10.21437/Interspeech.2023-1574. Link

Loza, G., Valdastri, P., Ali, S. Real-time surgical tool detection with multi-scale positional encoding and contrastive learning. Computer Methods in Biomechanics and Biomedical Engineering: Imaging and Visualization. 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.

Breen, J., Allen, K., Zucker, K., Adusumilli, P., Scarsbrook, A., Hall, G., Orsi, N.M. and Ravikumar, N., 2023. Artificial intelligence in ovarian cancer histopathology: a systematic review. npj Precision Oncology, 7(1), p.83.

Keighley, J., de Kamps, M., Wright, A., & Treanor, D. 2023. 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.

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);

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.

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

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.

Aubreville, M., N. Stathonikos, C.A. Bertram, R. Klopfleisch, N. ter Hoeve, F. Ciompi, F. Wilm, C. Marzahl, T.A. Donovan, A. Maier, J. Breen, N. Ravikumar, Y. Chung, J. Park, R. Nateghi, F. Pourakpour, R.H.J. Fick, S. Ben Hadj, M. Jahanifar, A. Shephard, J. Dexl, T. Wittenberg, S. Kondo, M.W. Lafarge, V.H. Koelzer, J. Liang, Y. Wang, X. Long, J. Liu, S. Razavi, A. Khademi, S. Yang, X. Wang, R. Erber, A. Klang, K. Lipnik, P. Bolfa, M.J. Dark, G. Wasinger, M. Veta, and K. Breininger, Mitosis domain generalization in histopathology images — The MIDOG challenge. Medical Image Analysis, 2023. 84: p.102699.

Broad, A., Wright, A.I., de Kamps, M. and Treanor, D., 2022. Attention-guided sampling for colorectal cancer analysis with digital pathology. Journal of Pathology Informatics, 13, p.100110.

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.

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,

Hancox, Z., Relton, S.D. 2022. Temporal Graph-Based CNNs (TG-CNNs) for Online Course Dropout Prediction. In Foundations of Intelligent Systems: 26th International Symposium, ISMIS 2022, Cosenza, Italy, October 3–5, 2022, Proceedings. Springer-Verlag, Berlin, Heidelberg, 357–367.

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.

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.

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.

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

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.

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). Link

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: 23919/CinC53138.2021.9662844