The coexistence of multiple medical conditions in an individual presents a complex challenge in healthcare. This research aims to enhance the analysis of comorbidity treatment plans by capturing nuanced interactions between different medical conditions and treatment interventions. Reaction systems provide a formal framework for modelling and analysing systems in which the dynamics is driven by promotion/inhibition mechanisms and external intervention of context processes. This study explores the integration of guards into context processes to increase the expressiveness of the formalism in order to analyse treatment plans for comorbidities. Through the analysis of combined clinical guidelines for atrial fibrillation and hypertension, we demonstrate the applicability and utility of this approach in optimizing patient care and improving health outcomes in the context of complex medical scenarios.
Bowles, J., Brodo, L., Bruni, R., Falaschi, M., Gori, R., Milazzo, P. (2024). Enhancing Reaction Systems with Guards for Analysing Comorbidity Treatment Strategies. In Computational Methods in Systems Biology (pp.27-44). Cham : Springer [10.1007/978-3-031-71671-3_3].
Enhancing Reaction Systems with Guards for Analysing Comorbidity Treatment Strategies
Falaschi M.;
2024-01-01
Abstract
The coexistence of multiple medical conditions in an individual presents a complex challenge in healthcare. This research aims to enhance the analysis of comorbidity treatment plans by capturing nuanced interactions between different medical conditions and treatment interventions. Reaction systems provide a formal framework for modelling and analysing systems in which the dynamics is driven by promotion/inhibition mechanisms and external intervention of context processes. This study explores the integration of guards into context processes to increase the expressiveness of the formalism in order to analyse treatment plans for comorbidities. Through the analysis of combined clinical guidelines for atrial fibrillation and hypertension, we demonstrate the applicability and utility of this approach in optimizing patient care and improving health outcomes in the context of complex medical scenarios.
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https://hdl.handle.net/11365/1275914