Search WestminsterResearch

Ogunbiyi, O., Basukoski, A. and Chaussalet, T.J. 2020. Investigating the Diffusion of Workload-Induced Stress—A Simulation Approach. Information. 12 (1) 11. https://doi.org/10.3390/info12010011

Urumov, G., Panagiotis Chountas and Chaussalet, T.J. 2025. Fuzzy Amplitudes and Kernels in Fractional Brownian Motion: Theoretical Foundations. Symmetry. 17 (4) 550. https://doi.org/10.3390/sym17040550

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

Worrall, P. and Chaussalet, T.J. 2015. A structured review of long-term care demand modelling. Health Care Management Science. 18 (2), pp. 173-194. https://doi.org/10.1007/s10729-014-9299-6

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

Ogunbiyi, O., Basukoski, A. and Chaussalet, T.J. 2021. An Exploration of Ethical Decision Making with Intelligence Augmentation. Social Sciences. 10 (2) 57. https://doi.org/10.3390/socsci10020057

Aldraimli, M., Soria, D., Parkinson, J., Thomas, E.L., Bell, J.D., Dwek, M. and Chaussalet, T.J. 2020. Machine Learning Prediction of Susceptibility to Visceral Fat Associated Diseases. Health and Technology. 10, pp. 925-944. https://doi.org/10.1007/s12553-020-00446-1

Urumov, G., Chountas, P. and Chaussalet, T.J. 2025. Fuzzy Amplitudes and Kernels in Fractional Brownian Motion: Theoretical Foundations. Symmetry. 17 (4) 550. https://doi.org/10.3390/sym17040550

Mesgarpour, M., Chaussalet, T.J. and Chahed, S. 2019. Temporal Comorbidity-Adjusted Risk of Emergency Readmission (T-CARER): A Tool for Comorbidity Risk Assessment. Applied Soft Computing. 79, pp. 163-185. https://doi.org/10.1016/j.asoc.2019.03.015

Nazyrova, Nodira, Chahed, Salma, Chausalet, Thierry and Dwek, Miriam 2024. Leveraging large language models for medical text classification: a hospital readmission prediction case. IEEE 14th International Conference on Pattern Recognition Systems (ICPRS). London, United Kingdom 15 - 18 Jul 2024 IEEE . https://doi.org/10.1109/icprs62101.2024.10677826

Dalton, S. 2018. Modelling the Perinatal Network System. PhD thesis University of Westminster Computer Science https://doi.org/10.34737/q559v

Aldraimli, M. 2023. Predictive Modelling Approach to Data-Driven Computational Preventive Medicine. PhD thesis University of Westminster Computer Science and Engineering https://doi.org/10.34737/w4ww2

Bolotov, A. Bolotov, A. (ed.) 2020. Proceedings of the 4th Student-STAFF Research Conference 2020 School of Computer Science and Engineering SSRC2020. University of Westminster.

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

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