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Nazyrova, N., Chahed, S., Chaussalet, T. and Dwek, M. 2024. Leveraging large language models for medical text classification: a hospital readmission prediction case. The IEEE 14th International Conference on Pattern Recognition Systems. London, United Kingdom 15 - 18 Jul 2024 IEEE .

Dianati-Nasab, Mostafa, Salimifard, Khodakaram, Mohammadi, Reza, Saadatmand, Sara, Fararouei, Mohammad, Hosseini, Kosar S., Jiavid-Sharifi, Behshid, Chaussalet, Thierry and Dehdar, Samira 2024. Machine learning algorithms to uncover risk factors of breast cancer: insights from a large case-control study. Frontiers in Oncology. 13 1276232. https://doi.org/10.3389/fonc.2023.1276232

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

Nazyrova, N., Chahed, S., Dwek, M., Getting, S. and Chaussalet, T. 2023. Discovering Drug-Drug Interactions Using Association Rule Mining from Electronic Health Records. The 17th International Conference on Innovations in Intelligent Systems and Applications. Hammamet, Tunisia 20 - 23 Sep 2023 IEEE . https://doi.org/10.1109/inista59065.2023.10310637

Kandasamy, Nichalini, Chaussalet, Thierry and Basukoski, Artie 2023. A Conceptual Framework to Predict Disease Progressions in Patients with Chronic Kidney Disease, Using Machine Learning and Process Mining. in: Healthcare Transformation with Informatics and Artificial Intelligence IOS Press. pp. 190-193

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

Noorain, S., Scaparra, M.P. and Kotiadis, K. 2022. Mind the gap: a review of optimisation in mental healthcare service delivery. Health Systems. 12 (2), pp. 133-166. https://doi.org/10.1080/20476965.2022.2035260

Vali, Masoumeh, Salimifard, Khodakaram, Gandomi, Amir H and Chaussalet, Thierry J 2022. Application of job shop scheduling approach in green patient flow optimization using a hybrid swarm intelligence. Computers & industrial engineering. 172, p. 108603. https://doi.org/10.1016/j.cie.2022.108603

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

Aldraimli, Mahmoud, Osman, Sarah, Grishchuck, Diana, Ingram, Samuel, Lyon, Robert, Mistry, Anil, Oliveira, Jorge, Samuel, Robert, Shelley, Leila E A, Soria, Daniele, Dwek, Miriam V, Aguado-Barrera, Miguel E, Azria, David, Chang-Claude, Jenny, Dunning, Alison, Giraldo, Alexandra, Green, Sheryl, Gutiérrez-Enríquez, Sara, Herskind, Carsten, van Hulle, Hans, Lambrecht, Maarten, Lozza, Laura, Rancati, Tiziana, Reyes, Victoria, Rosenstein, Barry S, de Ruysscher, Dirk, de Santis, Maria C, Seibold, Petra, Sperk, Elena, Symonds, R Paul, Stobart, Hilary, Taboada-Valadares, Begoña, Talbot, Christopher J, Vakaet, Vincent J L, Vega, Ana, Veldeman, Liv, Veldwijk, Marlon R, Webb, Adam, Weltens, Caroline, West, Catharine M, Chaussalet, Thierry J, Rattay, Tim and REQUITE consortium 2022. Development and Optimization of a Machine-Learning Prediction Model for Acute Desquamation After Breast Radiation Therapy in the Multicenter REQUITE Cohort. Advances in radiation oncology. 7 (3) 100890. https://doi.org/10.1016/j.adro.2021.100890

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

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

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

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

Ogunbiyi, Oluniyi 2022. Contextual and Ethical Issues with Predictive Process Monitoring. PhD thesis University of Westminster School of Computer Science and Engineering https://doi.org/10.34737/vqy62

Pandey, Sanjib Raj, Smith, Alan, Gall, Edmund Nigel, Bhatnagar, Ajay and Chaussalet, Thierry 2022. A Conceptual Framework to Predict Mental Health Patients' Zoning Classification. Studies in Health Technology and Informatics. 289, pp. 321-324. https://doi.org/10.3233/SHTI210924

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

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., 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, Niyi, Basukoski, Artie and Chaussalet, Thierry 2021. Incorporating spatial context into remaining-time predictive process monitoring. 36th Annual ACM Symposium on Applied Computing. Virtual Event Republic of Korea 22 - 26 Mar 2021 ACM. https://doi.org/10.1145/3412841.3441933