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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

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

Bolotov, Alexander 2022. On the Expressive Power of the Normal Form for Branching-Time Temporal Logics. Electronic Proceedings in Theoretical Computer Science. 358, pp. 254-269. https://doi.org/10.4204/eptcs.358.19

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

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

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

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

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

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

Bolotov, A. and Gorchakov, A. 2018. Tuning Natural Deduction Proof Search by Analytic Methods. The 25th Workshop on Automated Reasoning: Bridging the Gap between Theory and Practice. University of Cambridge Apr 2018 University of Cambridge.

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

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

Mesgarpour, M. 2017. Predictive Risk Modelling of Hospital Emergency Readmission, and Temporal Comorbidity Index Modelling Using Machine Learning Methods. PhD thesis University of Westminster Computer Science https://doi.org/10.34737/q3031

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

Guida, D. and Basukoski, A. 2017. WEIGHTBIT: An advancement in wearable technology. IEEE 30th International Symposium on Computer-Based Medical Systems. Thessaloniki, Greece 22 - 24 Jun 2017 IEEE . https://doi.org/10.1109/CBMS.2017.85

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.

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.

Bolotov, A. (ed.) 2014. Proceedings of the Joint Automated Reasoning Workshop and Deduktionstreffen: As part of the Vienna Summer of Logic – IJCAR 23-24 July 2014. IJCAR.