List of papers published in collaboration with Data Science Unit Expand all Collapse all Journal Marshall, A. et al. Income Trajectories and Precarity in Later life. Journal of Population Ageing (2024). doi: 10.1007/s12062-023-09437-2 Gilgannon, J., Freitas, D., Rizzo, R.E., Wheeler, J., Butler, I.B., Seth, S., Marone, F., Schlepütz, C.M., McGill, G., Watt, I. and Plümper, O., 2023. Elastic stresses can form metamorphic fabrics. Geology (2023), doi: https://doi.org/10.1130/G51612.1 MacRae C, Morales D, Mercer SW, Lone N, Lawson A, Jefferson E, et al. Impact of data source choice on multimorbidity measurement: a comparison study of 2.3 million individuals in the Welsh National Health Service. BMC Medicine ;21(1):309 (2023), doi: 10.1186/s12916-023-02970-z Docherty A. B. et al., "Patient emergency health-care use before hospital admission for COVID-19 and long-term outcomes in Scotland: a national cohort study" in The Lancet Digital Health, Volume 5, Issue 7, July 2023, Pages e446-e457 (2023), doi: 10.1016/S2589-7500(23)00051-1 McGivern K. G. et al., "Applying Artificial Intelligence to Big Data in Hepatopancreatic and Biliary Surgery: A Scoping Review" in Artificial Intelligence Surgery, 3(1):27-47 (2023), doi: 10.20517/ais.2022.39 N. C. Jenkins et al., "Computational Fluorescence Suppression in Shifted Excitation Raman Spectroscopy," in IEEE Transactions on Biomedical Engineering (2023), doi: 10.1109/TBME.2023.3243866. Adams, A., Kufcsak, A., Ehrlich, K., Dhaliwal, K., & Seth, S. Simultaneous Spectral Temporal Modelling for a Time-Resolved Fluorescence Emission Spectrum. IEEE Transactions on Biomedical Engineering (2023). doi: 10.1109/TBME.2023.3244664 Zhang, R., Seth, S., & Cumby, J. (2022). Grouped representation of interatomic distances as a similarity measure for crystal structures. Digital Discovery. doi: 10.1039/D2DD00054G Swann, O. V. et al. Studying the Long-term Impact of COVID-19 in Kids (SLICK). Healthcare use and costs in children and young people following community-acquired SARS-CoV-2 infection: protocol for an observational study using linked primary and secondary routinely collected healthcare data from England, Scotland and Wales. BMJ Open 12, e063271 (2022). doi: 10.1136/bmjopen-2022-063271 Fish, M. et al. Coronavirus disease 2019 subphenotypes and differential treatment response to convalescent plasma in critically ill adults: secondary analyses of a randomized clinical trial. Intensive Care Med (2022) doi:10.1007/s00134-022-06869-w Wood, H. A. C. et al. Tri‐mode optical biopsy probe with fluorescence endomicroscopy, Raman spectroscopy, and time‐resolved fluorescence spectroscopy. Journal of Biophotonics (2022) doi:10.1002/jbio.202200141 Watmough, G.R., Hagdorn, M., Brumhead, J. et al. Using open-source data to construct 20 metre resolution maps of children’s travel time to the nearest health facility. Sci Data 9, 217 (2022). doi:10.1038/s41597-022-01274-w Millar, J. E. et al. Distinct clinical symptom patterns in patients hospitalised with COVID-19 in an analysis of 59,011 patients in the ISARIC-4C study. Sci Rep 12, 6843 (2022) don:10.1038/s41598-022-08032-3. Neal, I., Seth, S., Watmough, G. & Diallo, M. S. Census-independent population estimation using representation learning. Sci Rep 12, 5185 (2022) doi:10.1038/s41598-022-08935-1. Jiang, Q. et al. Prediction of the performance of pre‐packed purification columns through machine learning. J of Separation Science (2022) doi:10.1002/jssc.202100864. Swann, O. V. et al. Clinical characteristics of children and young people admitted to hospital with covid-19 in United Kingdom: prospective multicentre observational cohort study. BMJ m3249 (2020) doi:10.1136/bmj.m3249. Boufea, K., Seth, S. & Batada, N. N. scID Uses Discriminant Analysis to Identify Transcriptionally Equivalent Cell Types across Single-Cell RNA-Seq Data with Batch Effect. iScience 23, 100914 (2020) doi:10.1016/j.isci.2020.100914. Seth, S., Murray, I. & Williams, C. K. I. Model Criticism in Latent Space. Bayesian Anal. 14, 703–725 (2019) doi:10.1214/18-BA1124. Seth, S., Akram, A. R., Dhaliwal, K. & Williams, C. K. I. Estimating Bacterial and Cellular Load in FCFM Imaging. Journal of Imaging 4, 11 (2018) doi:10.3390/jimaging4010011. Conference Adams, A. et al. Differentiating Individual Fluorophores from a Heterogenous Signature on a Fibre-based Time Resolved Fluorescene Spectroscopy (TRFS) System. World Molecular Imaging Congress (2022) Choudhury, D. et al. Endoscopic sensing of distal lung physiology. J. Phys.: Conf. Ser. 1151, 012009 (2019) doi:10.1088/1742-6596/1151/1/012009. Workshop Hemment, D., Vidmar, M., Panas, D., Murray-Rust, D., Belle, V. & Aylett, R. Agency and legibility for artists through Experiential AI. ACM Creativity & Cognition: 1st International Workshop on Explainable AI for the Arts (2023), xaixarts.github.io[pdf] Neal, I., Seth, S., Watmough, G. & Saliou Diallo, M. Towards Sustainable Census-Independent Population Estimation in Mozambique. Artificial Intelligence for Public Health (AI4PH) (2021) arXiv:2104.12696. Abstract Johnson L, Anand A, Marshall A, Seth S, Bach B. 1505 Using Patient And Public Involvement (PPI), Data And Design To Communicate About Frailty To The General Public . Age and Ageing, Jul;52(Supplement_2):afad104-074 (2023). Rizvi, A. et al. Strain ratio distributions can elegantly describe the effect of lesion location and size in femoral metastases. 28th Congress of the European Society of Biomechanics (2023) Tam, J., Centola, J., Kurudzhu, H., Watson, N., MacKenzie, J., Green, A., Summers, D., Barria, M., Seth, S., Smith, C., Pal, S. (2023, May 10-12). Deep learning survival prediction in sporadic Creutzfeldt-Jakob Disease. ABN/IICN Joint Annual Meeting (2023). Gilgannon, J. et al. A non-hydrostatic stress state forms fabrics during metamorphic reactions. European Geosciences Union (EGU) General Assembly (2023) Avramidis, N. et al. Genomic Stratification in Critical Ill COVID-19 Patients. 14th International Congress of Human Genetics (ICHG) (2023) Turnbull, C. et al. 616 Addressing Challenges to Enable Better Use of Routinely Collected Clinical Photographs: Evaluating the Largest Cleft Dataset for Machine Learning Analysis. British Journal of Surgery 109, znac269.310 (2022). Panas, D., Seth, S., Watmough, G. & Rush, D. Assessing the Utility of Open-Source Geo-Spatial Data for AI-Driven Estimation of Fire Spread Risk in Informal Settlements. Proceedings of the 41st EARSeL Symposium (2022). Przybylski, A. et al. Stratification of Fibrotic Lung Disease: Integration of Molecular Endotyping and Quantitative CT via Machine Learning. in Futuristic Medicine symposium, Royal College of Physicians Edinburgh (2019). Preprint Zhang, R., Seth, S. & Cumby, J. Grouped representation of interatomic distances as a similarity measure for crystal structures. (2022) doi:10.26434/chemrxiv-2022-9m4jh. Yang, Y., Seth, S., Butler, I. B. & Fusseis, F. Fast Segmentation of 4D Microtomography Volumes from Core-flooding Experiments in Porous Rock using Convolutional Neural Network. (2021) doi:10.1002/essoar.10507074.1 This article was published on 2024-11-22
