Abstract
Chronic Obstructive Pulmonary Disease (COPD) is a progressive respiratory condition, ranking as the third leading cause of global morbidity and mortality. In this project, we simulate Real Clinical Trials using Virtual Clinical Trials (VCT) for COPD patients, offering possibilities not feasible in traditional trials, such as exploring treatment adherence levels and creating virtual cohorts with specific characteristics. We propose a cohort-based management strategy leveraging data analytics to identify patterns within the COPD patient population and advocate for employing a finite-state machine (FSM) approach to model COPD exacerbations. Further research and validation are crucial to refine and scale this integrated model.
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Asghar, M. H., Wong, A., Epelde, F., Taboada, M., del Rosario, D. I. R., & Luque, E. (2024). A Virtual Clinical Trial for Evaluation of Intelligent Monitoring of Exacerbation Level for COPD Patients. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 14834 LNCS, pp. 137–144). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-63759-9_17
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