Health and Social Care Modelling

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

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

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

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

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.

T. Cui, R. Bai, S. Ding, A. Parkes, R. Qu, He, F. and J. Li 2020. A Hybrid Combinatorial Approach to a Two-Stage Stochastic Portfolio Optimization Model with Uncertain Asset Prices. Soft Computing. 24, pp. 2809-2831. https://doi.org/10.1007/s00500-019-04517-y

Salem, H., Caddeo, G., McFarlane, J., Patel, K., Cochrane, L., Soria, D., Henley, M. and Lund, J. 2018. A multicentre integration of a computer-led follow-up of prostate cancer is valid and safe. BJU international. 122 (3), pp. 418-426 BJU14157. https://doi.org/10.1111/bju.14157

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

Radhakrishnan Sujatha, Jyotir Moy Chatterjee, Angelopoulou, A., Kapetanios, E., Parvathaneni Naga Srinivasu and Duraisamy Jude Hemanth 2023. A transfer learning-based system for grading breast invasive ductal carcinoma. IET Image Processing. 17 (7), pp. 1979-1990. https://doi.org/10.1049/ipr2.12660

Al Batat, R., Angelopoulou, A., Premkumar, S., Hemanth, J. and Kapetanios, D.E. 2022. An End-to-End Automated License Plate Recognition System Using YOLO Based Vehicle and License Plate Detection with Vehicle Classification. Sensors. 22 9477. https://doi.org/10.3390/s22239477

Liu, J., Xu, B., Zheng, C., Gong, Y., Garibaldi, J.M., Soria, D., Green, A., Ellis, I.O., Zou, W. and Qiu, G. 2019. An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA. IEEE Transactions on Medical Imaging. 38 (2), pp. 617-628. https://doi.org/10.1109/TMI.2018.2868333

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

Roeva, O., Vassilev, P. and Chountas, P. 2017. Application of Topological Operators over Data from InterCriteria Analysis. Christiansen, H., Jaudoin, H., Chountas, P., Andreasen, T. and Legind Larsen, H. (ed.) 12th International Conference, FQAS 2017. London, UK 21 - 22 Jun 2017 Springer. https://doi.org/10.1007/978-3-319-59692-1_19

Alzebdi, M., Chountas, P. and Atanassov, K.T. 2012. Approximate XML query matching and rewriting using Intuitionistic Fuzzy Trees. 6th IEEE International Conference on Intelligent Systems (IS). Sofia, Bulgaria 06 - 08 Sep 2012 IEEE . https://doi.org/10.1109/IS.2012.6335216

Alzebdi, M., Chountas, P. and Atanassov, K.T. 2013. Arc-Based Soft XML Pattern Matching. Larsen, H.L., Martin-Bautista, M.J., Amparo Vila, M., Andreasen, T. and Christiansen, H. (ed.) 10th International Conference on Flexible Query Answering Systems, FQAS 2013. Granada, Spain 18 - 20 Sep 2013 Springer. https://doi.org/10.1007/978-3-642-40769-7_28

Chishti, I., Basukoski, A. and Chaussalet, T.J. 2016. Business Process Modelling 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.

Vali, M., Salimifard, K. and Chaussalet, T. 2021. Carbon Footprints in Emergency Departments: A Simulation-Optimization Analysis. in: Masmoudi M., Jarboui B. and Siarry P. (ed.) Operations Research and Simulation in Healthcare Springer. pp. 193-207

Worrall, P. and Chaussalet, T.J. 2017. Care Home Quality Scorecard: A scorecard inspired approach to benchmark care home quality. Operational Research Applied to Health Services. Bath, UK 24 - 28 Jul 2017

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

Agrawal, U., Soria, D., Wagner, C., Garibaldi, J.M., Ellis, I.O., Bartlett, J.M.S., Cameron, D., Rakha, E.A. and Green, A.R. 2019. Combining Clustering and Classification Ensembles: A Novel Pipeline to Identify Breast Cancer Profiles. Artificial Intelligence in Medicine. 97, pp. 27-37. https://doi.org/10.1016/j.artmed.2019.05.002

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

Agrawal, U., Pinar, A.J., Wagner, C., Havens, T.C., Soria, D. and Garibaldi, J.M. 2018. Comparison of Fuzzy Integral-Fuzzy Measure based Ensemble Algorithms with the State-of-the-art Ensemble Algorithms. Medina, J., Ojeda-Aciego, M., Verdegay, J.L., Perfilieva, I., Bouchon-Meunier, B. and Yager, R.R. (ed.) 17th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems. Cadiz, Spain 11 - 15 Jun 2018 Springer. https://doi.org/10.1007/978-3-319-91479-4

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

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

Liu, J.-F., Dineen, R.A., Avula, S., Chambers, T., Dutta, M., Jaspan, T., MacArthur, D.C., Howarth, S., Soria, D., Quinlan, P., Harave, S., Ong, C.C., Mallucci, C.L., Kumar, R., Pizer, B. and Walker, D.A. 2018. Development of a pre-operative scoring system for predicting risk of post-operative paediatric cerebellar mutism syndrome. British Journal of Neurosurgery. 32 (1), pp. 18-27. https://doi.org/10.1080/02688697.2018.1431204

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

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

Chaussalet, T.J., Mesgarpour, M., Worrall, P. and Chahed, S. 2017. Emergency Readmission for Integrated Care (ERIC) Model: Using an Automated Feature Generation & a Multi-Task Learner. Operational Research Applied to Health Services 2017. Bath, UK 24 - 28 Jul 2017

Chahed, S., Marcon, E., Sahin, E., Feillet, D. and Dallery, Y. 2009. Exploring new operational research opportunities within the Home Care context: the chemotherapy at home. Health Care Management Science. 12 (2), pp. 179-191. https://doi.org/10.1007/s10729-009-9099-6

Christiansen, H., Jaudoin, H., Chountas, P., Andreasen, T. and Larsen, H.L. (ed.) 2017. Flexible Query Answering Systems: 12th International Conference, FQAS 2017, London, UK, June 21–22, 2017, Proceedings. Berlin, Heidelberg Springer.

Agrawal, U., Wagner, C., Garibaldi, J.M. and Soria, D. 2019. Fuzzy Integral Driven Ensemble Classification using A Priori Fuzzy Measures. International Conference on Fuzzy Systems (FUZZ-IEEE 2019). 23 - 26 Jun 2019 IEEE . https://doi.org/10.1109/FUZZ-IEEE.2019.8858821

Chountas, P., Atanassov, K.T., Sotirova, E. and Bureva, V. 2015. Generalized Net Model of an Expert System Dealing with Temporal Hypothesis. Andreasen, T., Christiansen, H., Kacprzyk, J., Larsen, H., Pasi, G., Pivert, O., De Tré, G., Vila, M.A., Yazici, A. and Zadrozny, S. (ed.) 11th International Conference FQAS 2015. Cracow, Poland 26 - 28 Oct 2015 Springer. https://doi.org/10.1007/978-3-319-26154-6_36

Ribagin, S., Chountas, P. and Pencheva, T. 2017. Generalized Net Model of Muscle Pain Diagnosing. Christiansen, H., Jaudoin, H., Chountas, P., Andreasen, T. and Legind Larsen, H. (ed.) 12th International Conference, FQAS 2017. London, UK 21 - 22 Jun 2017 Springer. https://doi.org/10.1007/978-3-319-59692-1_24

Bureva, V., Sotirova, E. and Chountas, P. 2014. Generalized Net of the Process of Sequential Pattern Mining by Generalized Sequential Pattern Algorithm (GSP). Filev, D., Jabłkowski, J., Kacprzyk, J., Krawczak, M., Popchev, I., Rutkowski, L., Sgurev, V., Sotirova, E., Szynkarczyk, P. and Zadrozny, S. (ed.) 7th IEEE International Conference Intelligent Systems IS’2014. Warsaw, Poland 24 - 26 Sep 2014 Springer. https://doi.org/10.1007/978-3-319-11310-4_72

Figueredo, G.P., Agrawal, U., Mase, J.M.M., Mesgarpour, M., Wagner, C., Soria, D., Garibaldi, J.M., Siebers, P.O. and John, R.I. 2019. Identifying Heavy Goods Vehicle Driving Styles in the United Kingdom. IEEE Transactions on Intelligent Transportation Systems. 20 (9), pp. 3324-3336. https://doi.org/10.1109/TITS.2018.2875343

Atanassov, K.T., Atanassova, V., Chountas, P., Mitkova, M., Sotirova, E., Sotirov, S. and Stratiev, D. 2016. Intercriteria analysis over normalized data. Yager, R., Sgurev, V., Hadjiski, M. and Jotsov, V. (ed.) 2016 IEEE 8th International Conference on Intelligent Systems. Sofia, Bulgaria 04 - 06 Sep 2016 IEEE . https://doi.org/10.1109/IS.2016.7737480

Razak, T.R., Garibaldi, J.M., Wagner, C., Pourabdollah, A. and Soria, D. 2018. Interpretability and Complexity of Design in the Creation of Fuzzy Logic Systems - A User Study. 2018 IEEE Symposium Series on Computational Intelligence. Bengaluru, India 18 - 21 Nov 2018 IEEE . https://doi.org/10.1109/SSCI.2018.8628924

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

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

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