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Asaduzzaman, M. and Chaussalet, T.J. 2008. Modelling and performance measure of a perinatal network centre in the United Kingdom. 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. 506-511

Chishti, I., Basukoski, A., Chaussalet, T.J. and Beeknoo, N. 2018. Transformation of UML Activity Diagram for Enhanced Reasoning. Future Technologies Conference 2018. Vancouver, Canada 13 - 14 Nov 2018 Springer. https://doi.org/10.1007/978-3-030-02683-7_33

Mesgarpour, M., Chaussalet, T.J., Worrall, P. and Chahed, S. 2016. Predictive Risk Modelling for Integrated Care: a Structured Review. IEEE 29th International Symposium on Computer-Based Medical Systems. Dublin and Belfast 20 - 23 Jun 2016 IEEE . https://doi.org/10.1109/CBMS.2016.34

Chishti, I., Basukoski, A. and Chaussalet, T.J. 2017. Modeling and Optimizing Patient Flows. 8th Annual International Conference on ICT: Big Data, Cloud & Security. Singapore 21 - 22 Aug 2017 Global Science & Technology Forum. https://doi.org/10.5176/2251-2136_ICT-BDCS17.52

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

Demir, E., Chaussalet, T.J., Xie, H. and Millard, P.H. 2008. Emergency readmission criterion: a technique for determining emergency readmission time window. IEEE Transactions on Information Technology in Biomedicine. 12 (5), pp. 644-649. https://doi.org/10.1109/TITB.2007.911311

Chahed, S., Demir, E., Chaussalet, T.J., Millard, P.H. and Toffa, S.E. 2011. Measuring and modelling occupancy time in NHS continuing healthcare. BMC Health Services Research. 11 (155), p. 1. https://doi.org/10.1186/1472-6963-11-155

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

Ogunbiyi, O., Basukoski, A. and Chaussalet, T.J. 2022. Comparative analysis of clustering-based remaining-time predictive process monitoring approaches. International Journal of Business Process Integration and Management. 10 (3/4), pp. 230-241. https://doi.org/10.1504/IJBPIM.2021.124023

Aldraimli, M., Soria, D., Parkinson, J., Whitcher, B., Thomas, E.L., Bell, J.D., Chaussalet, T.J. and Dwek, M. 2019. Machine Learning Classification of Females Susceptibility to Visceral Fat Associated Diseases. MEDICON 2019: XV Mediterranean Conference on Medical and Biological Engineering and Computing. Coimbra, Portugal 26 - 28 Sep 2019 Springer. https://doi.org/10.1007/978-3-030-31635-8_81

Banziger, R.B., Basukoski, A. and Chaussalet, T.J. 2018. Discovering Business Processes in CRM Systems by leveraging unstructured text data. The 4th IEEE International Conference on Data Science and Systems (DSS-2018). Exeter, UK 28 - 30 Jun 2018 IEEE . https://doi.org/10.1109/HPCC/SmartCity/DSS.2018.00257

Chishti, I., Basukoski, A. and Chaussalet, T.J. 2018. Modeling Patient Flows: A Temporal Logic Approach. Journal On Computing. 6 (1) 1516. https://doi.org/10.5176/2251-3043_6.1.107

Islam, M.S., Chaussalet, T.J. and Koizumi, N. 2017. Towards a threshold climate for emergency lower respiratory hospital admissions. Environmental Research. 153, pp. 41-47. https://doi.org/10.1016/j.envres.2016.11.011

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

Adeyemi, S., Demir, E. and Chaussalet, T.J. 2013. Towards an evidence-based decision making healthcare system management: modelling patient pathways to improve clinical outcomes. Decision Support Systems. 55 (1), pp. 117-125. https://doi.org/10.1016/j.dss.2012.12.039

Nazyrova, N., Chaussalet, T.J. and Chahed, S. 2022. Machine Learning models for predicting 30-day readmission of elderly patients using custom target encoding approach. International Conference on Computational Science ICCS 2022. London, UK 21 - 23 Jun 2022 Springer. https://doi.org/10.1007/978-3-031-08757-8_12

Ogunbiyi, N., Basukoski, A. and Chaussalet, T.J. 2020. Investigating Social Contextual Factors in Remaining-Time Predictive Process Monitoring—A Survival Analysis Approach. Algorithms. 13 (11), p. e267. https://doi.org/10.3390/a13110267

He, F., Chaussalet, T.J. and Qu, R. 2019. Controlling Understaffing with Conditional Value-at-Risk Constraint for an Integrated Nurse Scheduling Problem under Patient Demand Uncertainty. Operations Research Perspectives. 6 (2019), p. 100119 100119. https://doi.org/10.1016/j.orp.2019.100119

Vali, M., Salimifard, K., Gandomi, A.H. and Chaussalet, T.J. 2022. Care process optimization in a cardiovascular hospital: an integration of simulation–optimization and data mining. Annals of Operations Research. 318, pp. 685-712. https://doi.org/10.1007/s10479-022-04831-z

Mesgarpour, M., Chaussalet, T.J. and Chahed, S. 2017. Ensemble Risk Model of Emergency Admissions (ERMER). International Journal of Medical Informatics. 103, pp. 65-77. https://doi.org/10.1016/j.ijmedinf.2017.04.010