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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 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.

Exploring the effect of temperature variations on unplanned asthma admissions

Book chapter

Islam, M.S., Chaussalet, T.J., Balta-Ozkan, N. and Demir, E. 2011. Exploring the effect of temperature variations on unplanned asthma admissions. in: Operational Research Information National Health Policy: proceedings of the 37th ORAHS conference School of Mathematics, Cardiff University. pp. 74-88

Computer Science and Engineering

Prof Thierry Chaussalet

Staff

0000-0001-5507-6158

Classification of Uterine Fibroids in Ultrasound Images Using Deep Learning Model

Conference paper

Dilna, K.T., Anitha, J., Angelopoulou, A., Chaussalet, T.J., Kapetanios, D.E. and Jude Hemanth, D. 2022. Classification of Uterine Fibroids in Ultrasound Images Using Deep Learning Model. International Conference on Computational Science ICCS 2022. London, UK 21 - 23 Jun 2022 Springer. https://doi.org/10.1007/978-3-031-08757-8_5

A tool for studying the effects of residents' attributes on patterns of length of stay in long-term care

Book chapter

Xie, H., Chaussalet, T.J. and Millard, P.H. 2005. A tool for studying the effects of residents' attributes on patterns of length of stay in long-term care. in: Tsymbal, A. and Cunningham, P. (ed.) Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems: 23-25 June 2005, Dublin, Ireland USA IEEE . pp. 473-478

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

Patients flow: a mixed-effects modelling approach to predicting discharge probabilities

Book chapter

Adeyemi, S., Chaussalet, T.J., Xie, H. and Millard, P.H. 2007. Patients flow: a mixed-effects modelling approach to predicting discharge probabilities. 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. 725-730

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

Super-Resolution Convolutional Network for Image Quality Enhancement in Remote Photoplethysmography based Heart Rate Estimation

Conference paper

Smera Premkumar, K., Angelopoulou, A., Chaussalet, T.J., Kapetanios, D.E. and Jude Hemanth, D. 2022. Super-Resolution Convolutional Network for Image Quality Enhancement in Remote Photoplethysmography based Heart Rate Estimation. International Conference on Computational Science ICCS 2022. London, UK 21 - 23 Jun 2022 Springer. https://doi.org/10.1007/978-3-031-08757-8_15

Determining readmission time window using mixture of generalised Erlang distribution

Book chapter

Demir, E., Chaussalet, T.J. and Xie, H. 2007. Determining readmission time window using mixture of generalised Erlang distribution. 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. 21-26

Towards effective capacity planning in a perinatal network centre

Journal article

Asaduzzaman, M., Chaussalet, T.J., Adeyemi, S., Chahed, S., Hawdon, J., Wood, D. and Robertson, N.J. 2010. Towards effective capacity planning in a perinatal network centre. Archives of Disease in Childhood. Fetal and Neonatal Edition. 95 (4), pp. F283-F287. https://doi.org/10.1136/adc.2009.161661

Discovering Process Models from Patient Notes

Conference paper

Banziger, R.B., Basukoski, A. and Chaussalet, T.J. 2023. Discovering Process Models from Patient Notes. 23rd International Conference on Computational Science (ICCS-23). Prague 03 - 05 Jul 2023 Springer. https://doi.org/10.1007/978-3-031-36024-4_18

Transfer Learning based Natural Scene Classification for Scene Understanding by Intelligent Machines

Conference paper

Surendran, R., Anitha, J., Angelopoulou, A., Chaussalet, T.J., Kapetanios, D.E. and Jude Hemanth, D. 2022. Transfer Learning based Natural Scene Classification for Scene Understanding by Intelligent Machines. International Conference on Computational Science ICCS 2022. London, UK 21 - 23 Jun 2022 Springer. https://doi.org/10.1007/978-3-031-08754-7_6

Design and implementation of a deep recurrent model for prediction of readmission in urgent care using electronic health records

Conference paper

Zebin, T. and Chaussalet, T.J. 2019. Design and implementation of a deep recurrent model for prediction of readmission in urgent care using electronic health 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.2019.8791466

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

Modelling the Home Health Care Nurse Scheduling Problem for Patients with Long-Term Conditions in the UK

Conference paper

He, F., Chaussalet, T.J. and Qu, R. 2019. Modelling the Home Health Care Nurse Scheduling Problem for Patients with Long-Term Conditions in the UK. 33rd International ECMS Conference on modelling and Simulation. Universita degli Studi della Campania, Caserta, Area of Napoli, Italy 11 - 14 Jun 2019 European Council for Modeling and Simulation. https://doi.org/10.7148/2019-0317

Risk Modelling Framework for Emergency Hospital Readmission, Using Hospital Episode Statistics Inpatient Data

Conference paper

Mesgarpour, M., Chaussalet, T.J. and Chahed, S. 2016. Risk Modelling Framework for Emergency Hospital Readmission, Using Hospital Episode Statistics Inpatient Data. IEEE 29th International Symposium on Computer-Based Medical Systems. Dublin and Belfast 20 - 23 Jun 2016 IEEE . https://doi.org/10.1109/CBMS.2016.21

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 system for patient management based discrete-event simulation and hierarchical clustering

Book chapter

Codrington-Virtue, A., Chaussalet, T.J., Millard, P.H., Whittlestone, P. and Kelly, J. 2006. A system for patient management based discrete-event simulation and hierarchical clustering. 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 2006, Salt Lake City, Utah. Proceedings Las Alamitos, USA IEEE . pp. 800-804