Outputs
Publications, talks, public engagement activities and other outputs generated by the CDT students.
Publications
2023
Eleanor Davyson, Xueyi Shen, Danni A. Gadd, Elena Bernabeu, Robert F. Hillary, Daniel L. McCartney, Mark Adams, Riccardo Marioni, and Andrew M. McIntosh (2023) Metabolomic Investigation of Major Depressive Disorder Identifies a Potentially Causal Association With Polyunsaturated Fatty Acids. Society of Biological Psychiatry. https://www.biologicalpsychiatryjournal.com/article/S0006-3223(23)00055-0/fulltext#%20 and mental Elf blog https://www.nationalelfservice.net/mental-health/depression/does-what-you-eat-affect-how-you-feel/
Justin Engelmann, Amos Storkey, Miguel O. Bernabeu (2023); Deep learning (DL) identifies age as key axis of perceptual variation in fundus images – without training on fundus images. Invest. Ophthalmol. Vis. Sci. 2023;64(9):PB004. https://iovs.arvojournals.org/article.aspx?articleid=2791219
Justin Engelmann, Amos Storkey, Miguel O. Bernabeu (2023); Exclusion of poor quality fundus images biases health research linking retinal traits and systemic health. Invest. Ophthalmol. Vis. Sci. 2023;64(8):2922. https://iovs.arvojournals.org/article.aspx?articleid=2789909
(Preprint) Burke, J., Engelmann, Justin, Hamid, C., Reid-Schachter, M., Pearson, T., Pugh, D., ... & MacCormick, I. J. (2023). Efficient and fully-automatic retinal choroid segmentation in OCT through DL-based distillation of a hand-crafted pipeline. arXiv preprint arXiv:2307.00904
Alessandro Fontanella, A Antoniou, W Li, J Wardlaw, G Mair, E Truco, A Storkey (2023) ACAT: Adversarial Counterfactual Attention for Classification and Detection in Medical Imaging. To appear at the International Conference on Machine Learning (ICML). https://arxiv.org/abs/2303.15421
Georges Bedran, Hans-Christof Gasser, Kenneth Weke, Tongjie Wang, Dominika Bedran, Alexander Laird, Christophe Battail, Fabio Massimo Zanzotto, Catia Pesquita, Håkan Axelson, Ajitha Rajan, David J. Harrison, Aleksander Palkowski, Maciej Pawlik, Maciej Parys, J. Robert O'Neill, Paul M. Brennan, Stefan N. Symeonides, David R. Goodlett, Kevin Litchfield, Robin Fahraeus, Ted R. Hupp, Sachin Kote, Javier A. Alfaro (2023) The Immunopeptidome from a Genomic Perspective: Establishing the Noncanonical Landscape of MHC Class I-Associated Peptides. Cancer Immunol Res (2023) 11 (6): 747–762. https://doi.org/10.1158/2326-6066.CIR-22-0621
(Preprint) Aryo Pradipta Gema, Michał Kobiela, Achille Fraisse, Ajitha Rajan, Diego A Oyarzún, Javier Antonio Alfaro, (2023). Vaxformer: Antigenicity-controlled Transformer for Vaccine Design Against SARS-CoV-2. ArXiv. https://arxiv.org/pdf/2305.11194.pdf
(Preprint) Aryo Pradipta Gema, Dominik Grabarczyk, Wolf De Wulf, and Piyush Borole, Javier Antonio Alfaro, Pasquale Minervini, Antonio Vergari, Ajitha Rajan, (2023) . Knowledge Graph Embeddings in the Biomedical Domain: Are They Useful? A Look at Link Prediction, Rule Learning, and Downstream Polypharmacy Tasks. ArXiv. https://arxiv.org/abs/2305.19979
(Preprint) Aryo Pradipta Gema, Luke Daines, Pasquale Minervini, Beatrice Alex (2023). Parameter-Efficient Fine-Tuning of LLaMA for the Clinical Domain. ArXiv. https://arxiv.org/pdf/2307.03042.pdf
(Preprint) Bryan M. Li, Isabel M. Cornacchia, Nathalie L. Rochefort, Arno Onken (2023) V1T: large-scale mouse V1 response prediction using a Vision Transformer. https://arxiv.org/abs/2302.03023
(Preprint) Filippo Corponi*, Bryan M. Li*, Gerard Anmella, Ariadna Mas, Miriam Sanabra, Eduard Vieta, INTREPIBD Group, Stephen M. Lawrie, Heather C. Whalley, Diego Hidalgo-Mazzei, Antonio Vergari (2023) Automated mood disorder symptoms monitoring from multivariate time-series sensory data: Getting the full picture beyond a single number. https://www.medrxiv.org/content/10.1101/2023.03.25.23287744v1
Gerard Anmella*, Filippo Corponi*, Bryan M. Li*, Ariadna Mas, Miriam Sanabra, Isabella Pacchiarotti, Marc Valentí, Iria Grande, Antoni Benabarre, Anna Giménez-Palomo, Marina Garriga, Isabel Agasi, Anna Bastidas, Myriam Cavero, Tabatha Fernández-Plaza, Néstor Arbelo, Miquel Bioque, Clemente García-Rizo, Norma Verdolini, Santiago Madero, Andrea Murru, Silvia Amoretti, Anabel Martínez-Aran, Victoria Ruiz, Giovanna Fico, Michele De Prisco, Vincenzo Oliva, Aleix Solanes, Joaquim Radua, Ludovic Samalin, Allan H. Young, Eduard Vieta, Antonio Vergari, Diego Hidalgo-Mazzei (2023) Exploring digital biomarkers of illness activity in mood episodes: hypotheses generating and model development study. Journal of Medical Internet Research (JMIR) mHealth and uHealth. https://www.medrxiv.org/content/10.1101/2023.03.25.23287744v1
Ondrej Bohdal, Yinbing Tian, Yongshuo Zong, Ruchika Chavhan, Da Li, Henry Gouk, Li Guo, Timothy Hospedales (2023) Meta Omnium: A Benchmark for General-Purpose Learning-to-Learn. IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023. https://openaccess.thecvf.com/content/CVPR2023/html/Bohdal_Meta_Omnium_A_Benchmark_for_General-Purpose_Learning-To-Learn_CVPR_2023_paper.html
2022
Laura Watson, Rayna Andreeva, Hao-Tsung Yang, Rik Sarkar, (Preprint) Differentially Private Shapley Values for Data Evaluation. https://arxiv.org/abs/2206.00511
Justin Engelmann, Alice D. McTrusty, Ian J. C. MacCormick, Emma Pead, Amos Storkey & Miguel O. Bernabeu (2022) Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning. Nature machine intelligence. https://www.nature.com/articles/s42256-022-00566-5
Justin Engelmann, Ana Villaplana-Velasco, Amos Storkey & Miguel O. Bernabeu (2022) Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation. Ophthalmic Medical Image Analysis. OMIA 2022. Lecture Notes in Computer Science, vol 13576. https://link.springer.com/chapter/10.1007/978-3-031-16525-2_9
Dominic Phillips, Hans-Christof Gasser, Sebestyén Kamp, Aleksander Pałkowski, Lukasz Rabalski, Diego A. Oyarzún, Ajitha Rajan, Javier Antonio Alfaro (2022) Generating Immune-aware SARS-CoV-2 Spike Proteins for Universal Vaccine Design. Proceedings of the 1st Workshop on Healthcare AI and COVID-19, ICML 2022, PMLR 184:100-116, 2022. https://proceedings.mlr.press/v184/phillips22a.html
Olivier Labayle Pabet, Kelsey Tetley-Campbell, Mark Van Der Laan, Chris P. Ponting, Sjoerd Viktor Beentjes, Ava Khamseh, (Preprint) Dispensing with unnecessary assumptions in population genetics analysis. https://www.biorxiv.org/content/10.1101/2022.09.12.507656v1
Bryan M. Li, Leonardo V. Castorina, Maria del C. Valdés-Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael T. Thrippleton, Michael Stringer, Joanna M. Wardlaw (2022) Deep attention super-resolution of brain magnetic resonance images acquired under clinical protocols. Frontiers in Computational Neuroscience. https://www.frontiersin.org/articles/10.3389/fncom.2022.887633/full
Bryan M. Li*, Filippo Corponi*, Gerard Anmella, Ariadna Mas, Miriam Sanabra, Diego Hidalgo-Mazzei, Antonio Vergari (2022) Inferring mood disorder symptoms from multivariate time-series sensory data. NeurIPS Workshop on Learning from Time Series for Health. https://openreview.net/forum?id=awjU8fCDZjS
2021
Beltramo, G., Skraba, P., Andreeva, Rayna, Sarkar, R., Giarratano, Y. and Bernabeu, M., (2021). Euler characteristic surfaces. Foundations of Data Sciences http://dx.doi.org/10.3934/fods.2021027
Saadat-Yazdi A., Andreeva Rayna, Sarkar R. (2021) Topological Detection of Alzheimer’s Disease Using Betti Curves. In: Reyes M. et al. (eds) Interpretability of Machine Intelligence in Medical Image Computing, and Topological Data Analysis and Its Applications for Medical Data. IMIMIC 2021, TDA4MedicalData 2021. Lecture Notes in Computer Science, vol 12929. Springer, Cham. https://doi.org/10.1007/978-3-030-87444-5_12
(Preprint) PDBench: Evaluating Computational Methods for Protein Sequence Design. Leonardo Castorina, R Petrenas, K Subr, CW Wood
Angeletos Chrysaitis Nikitas, Jardri R, Denève S, Seriès P (2021) No increased circular inference in adults with high levels of autistic traits or autism. PLOS Computational Biology 17(9): e1009006. https://doi.org/10.1371/journal.pcbi.1009006
Filippo Corponi, Zorkina, Y., Stahl, D., Murru, A., Vieta, E., Serretti, A., Morozova, А., Reznik, A., Kostyuk, G. and Chekhonin, V.P. (2021). Frontal lobes dysfunction across clinical clusters of acute schizophrenia. Revista de Psiquiatría y Salud Mental. https://doi.org/10.1016/j.rpsm.2021.12.002
Matúš Falis, Dong, H., Birch, A., & Alex, B. (Accepted/In press). CoPHE: A Count-Preserving Hierarchical Evaluation Metric in Large-Scale Multi-Label Text Classification. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (EMNLP 2021)
(Preprint) Challenges of building medical image datasets for development of deep learning software in stroke. Wenwen Li, Grant Mair, Alessandro Fontanella, Antreas Antoniou, Eleanor Platt , Chloe Martin, Paul Armitage , Emanuele Trucco, Amos Storkey, Joanna Wardlaw
Bryan M. Li, Theoklitos Amvrosiadis, Nathalie Rochefort, Arno Onken (2021) Neuronal Learning Analysis using Cycle-Consistent Adversarial Networks (Preprint). https://arxiv.org/abs/2111.13073
(Preprint) Super-Resolution of Magnetic Resonance Images Acquired Under Clinical Protocols using Deep Attention-based Method. Bryan Li, Leonardo Castorina, Maria del C. Valdés-Hernández, Una Clancy, Stewart J. Wiseman, Eleni Sakka, Amos J. Storkey, Daniela Jaime Garcia, Yajun Cheng, Fergus Doubal, Michael T. Thrippleton, Michael Stringer, Joanna M. Wardlaw medRxiv 2022.01.24.22269144; doi: https://doi.org/10.1101/2022.01.24.22269144
(Preprint) Designing human Sphingosine-1-phosphate lyases using a temporal Dirichlet variational autoencoder. Evgenii Lobzaev, Michael A. Herrera, Dominic J. Campopiano, Giovanni Stracquadanio bioRxiv 2022.02.14.480330; doi: https://doi.org/10.1101/2022.02.14.480330
Michael Stam, Wood C W, DE-STRESS: a user-friendly web application for the evaluation of protein designs, Protein Engineering, Design and Selection, Volume 34, 2021, gzab029, https://doi.org/10.1093/protein/gzab029
(Preprint) DNA Methylation scores augment 10-year risk prediction of diabetes. Yipeng Cheng, Danni A Gadd, Christian Gieger, Karla Monterrubio-Gómez, Yufei Zhang, Imrich Berta, Michael Stam, Natalia Szlachetka, Evgenii Lobzaev, Archie Campbell, Cliff Nangle, Rosie M Walker, Chloe Fawns-Ritchie, Annette Peters, Wolfgang Rathmann, David J Porteous, Kathryn L Evans, Andrew M McIntosh, Timothy I Cannings, Melanie Waldenberger, Andrea Ganna, Daniel L McCartney, Catalina A Vallejos, Riccardo E Marioni medRxiv 2021.11.19.21266469; doi: https://doi.org/10.1101/2021.11.19.21266469
2020
Andreeva, Rayna, Fontanella, Alessandro, Giarratano Y., Bernabeu M.O. (2020) DR Detection Using Optical Coherence Tomography Angiography (OCTA): A Transfer Learning Approach with Robustness Analysis. In: Fu H., Garvin M.K., MacGillivray T., Xu Y., Zheng Y. (eds) Ophthalmic Medical Image Analysis. OMIA 2020. Lecture Notes in Computer Science, vol 12069. Springer, Cham. https://doi.org/10.1007/978-3-030-63419-3_2
Giarratano, Y., Pavel, A., Lian, J., Andreeva, Rayna, Fontanella, Alessandro, Sarkar, R., Reid, L., Forbes, S., Pugh, D., Farrah, T., Dhaun, N., Dhillon, B., MacGillivray, T. and Bernabeu, M., 2020. A Framework for the Discovery of Retinal Biomarkers in Optical Coherence Tomography Angiography (OCTA). Ophthalmic Medical Image Analysis, pp.155-164.OMIA 2020. Lecture Notes in Computer Science, vol 12069. Springer, Cham. https://doi.org/10.1007/978-3-030-63419-3_16
Fontanella, Alessandro, Pead, E.,Macgillivray, T., Bernabeu, M., & Storkey, A. (2020). Classification with a domain shift in medical imaging. Med-NeurIPS 2020: Medical Imaging meets NeurIPS Workshop http://www.cse.cuhk.edu.hk/~qdou/public/medneurips2020/43_Classification_with_a_domain_shift_in_medical_imaging.pdf
Talks
2023
Justin Engelmann: 'Exclusion of poor quality fundus images biases health research linking retinal traits and systemic health', ARVO annual meeting, 2023
Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', UK Biobank Eye & Vision Consortium meeting, 2023
2022
Rayna Andreeva: 'Topological data analysis for papillae classification', CAI4H, 2022
Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', AI and Machine Learning in Healthcare Summer School at the Cambridge Centre for AI in Medicine 2022
Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', Plenary of the VAMPIRE research group 2022
Alessandro Fontanella: 'ACAT: Adversarial counterfactual attention for classification and detection in medical imaging', CAI4H - Joint AI Health meeting 2022
Alessandro Fontanella: 'The Challenges and Applications of Deep Learning Methods on Medical Imaging for Acute Ischemic Stroke', Edinburgh Imaging Academy - NIS meeting 2022
Alessandro Fontanella: 'The Challenges and Applications of Deep Learning Methods on Medical Imaging for Acute Ischemic Stroke', HDR UK - Applied Analytics seminar 2022
Aryo Pradipta Gema: 'Knowledge-Augmented Clinical Language Models', Guest Lecturer at Bina Nusantara University 2023
Aryo Pradipta Gema: 'Knowledge Graph Embeddings in the Biomedical Domain', Guest Lecturer at Bina Nusantara University 2023
Bryan Li: 'Identifying digital biomarkers of illness activity and treatment response in bipolar disorder', UKRI AI CDTs in Healthcare Conference 2022
Angeletos Chrysaitis Nikitas: 'First impression bias in the development of perceptual priors', TEX2022: Bringing together Predictive Processes and Statistical Learning 2022
2021
Rayna Andreeva: 'Automatic papillae identification using discrete curvature analysis', Food Oral Processing, Early Career Researcher session 2021
Rayna Andreeva: A Geometric Approach to Papillae Identification in 3D Meshes, Young Researchers Forum, 37th Symposium on Computational Geometry 2021 https://cse.buffalo.edu/socg21/program.html
Matúš Falis: 'Towards Better Use of Ontological Structure in the Evaluation of Automated ICD Coding', HealTAC Healthcare Text Analytics Conference 2021
Alessandro Fontanella: 'Deep learning methods to identify ischemic stroke lesions from CT scans of the brain', SICSA Conference 2021
Evgenii Lobzaev: 'Primer on Variational Inference and its application to Deep Learning', 6th Winter School on Data Analytics DA 2021
Evgenii Lobzaev: 'AI-driven design of enzyme replacement therapies', SICSA Conference 2021
2020
Rayna Andreeva: 'DR Detection Using Optical Coherence Tomography Angiography (OCTA): A Transfer Learning Approach with Robustness Analysis', 7th MICCAI Workshop on Ophthalmic Medical Image Analysis (OMIA7)
Rayna Andreeva, Alessandro Fontanella: 'Identifying patient status using optical coherence tomography angiography (OCTA): A transfer learning approach', 12th SINAPSE Annual Scientific Meeting
Alessandro Fontanella: 'Classification with a domain shift in medical imaging', NEURIPS- Medical imaging meets NEURIPS workshop
Posters
2023
Justin Engelmann: 'Deep learning identifies age as a key axis of perceptual variation in fundus images – without training on fundus images', ARVO imaging in the eye pre-conference, 2023
2022
Aleksandra Sobieska: 'Development of a machine learning-based approach for the analysis of DNA replication in primary mammalian cells', Biomedical AI Research Summer Social Poster Session, 2022
Aleksandra Sobieska: 'Benchmarking of deconvolution algorithms for data-informed cell type composition of in vitro models for non-alcoholic fatty liver disease', Biomedical AI Research Poster Showcase, 2022
Justin Engelmann: 'Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning', Biomedical AI Research Poster Showcase, 2022
Justin Engelmann: 'Robust and Efficient Computation of Retinal Fractal Dimension Through Deep Approximation', Ophthalmic Medical Image Analysis workshop at the 25th International Conference on Medical Image Computing and Computer Assisted Intervention, 2022
Justin Engelmann: 'Detecting multiple retinal diseases in ultra-widefield fundus imaging and data-driven identification of informative regions with deep learning' Provost’s visit to the School of Informatics, 2022
Justin Engelmann: 'Parity in predictive performance is neither necessary nor sufficient for fairness', Algorithmic Fairness through the Lens of Causality and Privacy at the NeurIPS conference, 2022
Alessandro Fontanella: 'ACAT: Adversarial counterfactual attention for classification and detection in medical imaging', CAI4H, 2022
Olivier Labayle Pabet: 'Let’s remove unnecessary assumptions from population genetics studies', EMGM, 2022
Bryan Li: 'Inferring mood disorder symptoms from multivariate time-series sensory data', NeurIPS Workshop on Learning from Time Series for Health, 2022
Evgenii Lobzaev: 'Designing Human Sphingosine-1-phosphate Lyases Using Generative Deep Learning', Glycolipid and Sphingolipid Biology GRC
Leonardo Castorina: 'Machine Learning for Protein Design', APFED22
Matúš Falis: 'Horses to Zebras: Ontology-Guided Data Augmentation and Synthesis for ICD-9 Coding', ACL 2022
Michael Stam: 'Data-driven prediction of antibody expression', APFED22
Rayna Andreeva: 'Topological data analysis for papillae classification', CAI4H, 2022
Rayna Andreeva: 'Topological data analysis for papillae classification', Autumn poster session, online, AATRN 2022
Rayna Andreeva: 'Topological data analysis for papillae classification', Provost’s visit to the School of Informatics, 2022
Rayna Andreeva: 'Topological data analysis for papillae classification', Biomedical AI Research Poster Showcase, 2022
Rayna Andreeva: 'Applications of magnitude to neural networks', Topology of Data in Rome
Rayna Andreeva: 'Topological data analysis for papillae classification', SINAPSE Annual Scientific Meeting
Rayna Andreeva: 'Topological data analysis for papillae classification', Applied Topology in Będlewo 2022
2021
Rayna Andreeva: 'Automatic papillae identification using discrete curvature analysis', Food Oral Processing 2021, Early Career Researcher session
Domas Linkevicius: 'Modeling the dynamics of partially known systems via the integration of a system of ordinary differential equations into a recurrent neural network', CNS*2021
Domas Linkevicius: 'Combining neural ODEs and incomplete ODE systems to model complex, under-parameterised synaptic biochemical networks', Neuroscience 2021
Filippo Corponi: 'Definition of early age at onset in bipolar disorder according to distinctive neurodevelopmental pathways: insights from the FACE-BD study', French Congress of Psychiatry
Li W, Fontanella Alessandro, Antoniou A, Platt E., Martin C., Mair G., Trucco E., Storkey A., Wardlaw J.: 'Acute ischaemic stroke (AIS) lesion detection with a convolutional deep learning model', 7th European Stroke Organisation Conference ESOC 2021
Mair G., Li W., Martin C., Fontanella, Alessandro, Trucco E., Storkey A., Wardlaw J.: 'Challenges of delivering medical image sets for development of deep learning software in stroke', Artificial intelligence in practice 2021
Public Engagement and EDI initiatives
Aryo Pradipta Gema: 'Large Language Models and its biomedical applications' with Sutton Trust Summer School at University of Edinburgh: a speaker to introduce Large Language Models and ChatGPT as well as the potential clinical use cases.
Aryo Pradipta Gema: 'ChatGPT: A Biomedical AI Perspective' at University of Edinburgh: a speaker to introduce Large Language Models and ChatGPT as well as the potential clinical use cases (2023)
Bryan Li: Alan Turing Institute 2023-2024 Enrichment Scheme Placement award (2023-2024)
Michael Stam, Leo Castorina, Natalia Szlachetka and Team: "Programming Proteins" pubic exhibition at the Royal Society Summer Science Exhibition (2022).
Katarzyna Szymaniak: Co-Creation Workshop with IntellSensing Lab at Newcastle University (2021)
Rayna Andreeva, Natalia Szlachetka, Katarzyna Szymaniak: Panel participation: Women in AI event hosted by UCL (2020)
Rayna Andreeva: EDI in STEM: Race and Disability Workshop. Participation in an EDI workshop as part of the Women in STEM and CompSoc's equality, diversity, and inclusion (EDI) series with Dr Frantzana (2020)