Virtue, A., Chaussalet, T.J. and Kelly, J. 2011. A case study using simplified discrete-event simulation models as a tool to reconfigure health care services. in: Operational Research Information National Health Policy: proceedings of the 37th ORAHS conference School of Mathematics, Cardiff University.
Chaussalet, T.J., Xie, H. and Millard, P.H. 2006. A closed queueing network approach to the analysis of patient flow in health care systems. Methods of Information in Medicine. 45 (5), pp. 492-497.
Aldraimli, M., Nazyrova, N., Djumanov, A., Sobirov, I. and Chaussalet, T.J. 2022. A Comparative Machine Learning Modelling Approach for Patients' Mortality Prediction in Hospital Intensive Care Unit . Sotirov, S.S., Pencheva, T., Kacprzyk, J., Atanassov, K.T., Sotirova, E. and Staneva, G. (ed.) International Symposium on Bioinformatics and Biomedicine. Burgas, Bulgaria 08 - 10 Oct 2020 Springer. https://doi.org/10.1007/978-3-030-96638-6_2
Xie, H., Chaussalet, T.J. and Millard, P.H. 2005. A continuous time Markov model for the length of stay of elderly people in institutional long-term care. Journal of the Royal Statistical Society: Series A. 168 (1), pp. 51-61. https://doi.org/10.1111/j.1467-985X.2004.00335.x
Aldraimli, M., Soria, D., Grishchuck, D., Ingram, S., Lyon, R., Mistry, A., Oliveira, J., Samuel, R., Shelley, L.E.A., Osman, S., Dwek, M., Azria, D., Chang-Claude, J., Gutiérrez-Enríquez, S., De Santis, M.C., Rosenstein, B.S., De Ruysscher, D., Sperk, E., Symonds, R.P., Stobart, H., Vega, A., Veldeman, L., Webb, A, Christopher, J.T., West, C.M., Rattay, T., REQUITE consortium and Chaussalet, T.J. 2021. A Data Science Approach for Early-Stage Prediction of Patient’s Susceptibility to Acute Side Effects of Advanced Radiotherapy. Computers in Biology and Medicine. 135 104624. https://doi.org/10.1016/j.compbiomed.2021.104624
Demir, E., Chahed, S., Chaussalet, T.J., Toffa, S.E. and Fouladinajed, F. 2012. A decision support tool for health service re-design. Journal of Medical Systems. 36 (2), pp. 621-630. https://doi.org/10.1007/s10916-010-9526-8
Zebin, T., Rezvy, S. and Chaussalet, T.J. 2019. A deep learning approach for length of stay prediction in clinical settings from medical records. 16th IEEE International Conference on Computational Intelligence in Bioinformatics and Computational Biology. Certosa di Pontignano, Siena - Tuscany, Italy 09 - 11 Jul 2019 IEEE . https://doi.org/10.1109/CIBCB.2019.8791477
Pelletier, C., Chaussalet, T.J. and Xie, H. 2005. A framework for predicting gross institutional long-term care cost arising from known commitments at local authority level. Journal of the Operational Research Society. 56 (2), pp. 144-152. https://doi.org/10.1057/palgrave.jors.2601892
Chishti, I., Chaussalet, T.J. and Basukoski, A. 2016. A general framework for Business Process Modelling (BPM) based on Formal Temporal Theory with an application to Hospital Patient flows. 8th IMA International Conference on Quantitative Modelling in the Management of Health and Social Care. Asia House, London 21 - 23 Mar 2016 Institute of Mathematics and its Applications.
Demir, E., Chaussalet, T.J., Weingarten, N. and Kiss, T. 2009. A Grid implementation for profiling hospitals based on patient readmissions. in: McClean, S.I., Millard, P.H., El-Darzi, E. and Nugent, C. (ed.) Intelligent patient management Springer.
Asaduzzaman, M., Chaussalet, T.J. and Robertson, N.J. 2010. A loss network model with overflow for capacity planning of a neonatal unit. Annals of Operations Research. 178 (1), pp. 67-76. https://doi.org/10.1007/s10479-009-0548-x
Demir, E., Chaussalet, T.J., Xie, H. and Millard, P.H. 2006. A method for determining an emergency readmission time window for better patient management. in: Lee, D.J., Nutter, B., Antani, S., Mitra, S. and Archibald, J. (ed.) Nineteenth IEEE International Symposium on Computer-Based Medical Systems: 22-23 June June 2006, Salt Lake City, Utah. Proceedings Las Alamitos, USA IEEE . pp. 789-793
Xie, H., Chaussalet, T.J. and Millard, P.H. 2006. A model-based approach to the analysis of patterns of length of stay in institutional long-term care. IEEE Transactions on Information Technology in Biomedicine. 10 (3), pp. 512-518. https://doi.org/10.1109/TITB.2005.863820
Rathi, M. 2015. A novel framework for predicting patients at risk of readmission. PhD thesis University of Westminster Department of Computer Science https://doi.org/10.34737/9x22z
Chishti, I. 2019. A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows. PhD thesis University of Westminster School of Computer Science and Engineering https://doi.org/10.34737/qy760
Adeyemi, S. and Chaussalet, T.J. 2008. A random effects sensitivity analysis for patient pathways model. in: Proceedings of the 21st IEEE International Symposium on Computer-Based Medical Systems, IEEE CBMS 2008, Jyväskylä, 17-19 June 2008 Los Alamitos, USA IEEE . pp. 536-538
Mesgarpour, M., Chaussalet, T.J. and Chahed, S. 2014. A review of dynamic Bayesian network techniques with applications in healthcare risk modelling. 4th Student Conference on Operational Research (SCOR14). Nottingham, UK May 2–4, 2014 Schloss Dagstuhl - Leibniz-Zentrum fuer Informatik. https://doi.org/10.4230/OASIcs.SCOR.2014.89
Rathi, M. and Chaussalet, T.J. 2012. A risk analysis method for assessing risks based on interval-valued fuzzy number. in: 2012 IEEE International conference on computational intelligence and computing research (ICCIC), 18-20 December 2012, Coimbatore, India IEEE .
Xie, H., Chaussalet, T.J. and Rees, M. 2007. A semi-open queueing network approach to the analysis of patient flow in healthcare systems. in: Proceedings of the 20th IEEE International Symposium on Computer-Based Medical Systems. IEEE CBMS 2007, Maribor, Slovenia, 20-22 June 2007 Los Alamitos, USA IEEE . pp. 719-724
Xie, H., Chaussalet, T.J., Thompson, W.A. and Millard, P.H. 2007. A simple graphical decision aid for the placement of elderly people in long-term care. Journal of the Operational Research Society. 58 (4), pp. 446-453. https://doi.org/10.1057/palgrave.jors.2602179