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A case study using simplified discrete-event simulation models as a tool to reconfigure health care services

Book chapter

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.

A closed queueing network approach to the analysis of patient flow in health care systems

Article

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.

A Comparative Machine Learning Modelling Approach for Patients' Mortality Prediction in Hospital Intensive Care Unit

Conference paper

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

A continuous time Markov model for the length of stay of elderly people in institutional long-term care

Article

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

A Data Science Approach for Early-Stage Prediction of Patient’s Susceptibility to Acute Side Effects of Advanced Radiotherapy

Journal article

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

A decision support tool for health service re-design

Journal article

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

A deep learning approach for length of stay prediction in clinical settings from medical records

Conference paper

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

A framework for predicting gross institutional long-term care cost arising from known commitments at local authority level

Journal article

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

A general framework for Business Process Modelling (BPM) based on Formal Temporal Theory with an application to Hospital Patient flows

Conference poster

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.

A Grid implementation for profiling hospitals based on patient readmissions

Book chapter

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.

A loss network model with overflow for capacity planning of a neonatal unit

Article

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

A method for determining an emergency readmission time window for better patient management

Book chapter

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

A model-based approach to the analysis of patterns of length of stay in institutional long-term care

Article

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

A novel framework for predicting patients at risk of readmission

PhD thesis

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

A Process Modelling Framework Based on Point Interval Temporal Logic with an Application to Modelling Patient Flows

PhD thesis

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

A random effects sensitivity analysis for patient pathways model

Book chapter

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

A review of dynamic Bayesian network techniques with applications in healthcare risk modelling

Conference paper

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

A risk analysis method for assessing risks based on interval-valued fuzzy number

Book chapter

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 .

A semi-open queueing network approach to the analysis of patient flow in healthcare systems

Book chapter

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

A simple graphical decision aid for the placement of elderly people in long-term care

Journal article

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