Please use this identifier to cite or link to this item: https://scidar.kg.ac.rs/handle/123456789/22896
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dc.contributor.authorFilipovic, Nenad-
dc.contributor.authorSaveljic I.-
dc.contributor.authorGeroski, Tijana-
dc.contributor.authorTomasevic, Smiljana-
dc.contributor.authorMilosevic, Miljan-
dc.contributor.authorMilicevic, Bogdan-
dc.contributor.authorProdanovic, Momcilo-
dc.contributor.authorMijailovich, Srboljub-
dc.contributor.authorKojić, Miloš-
dc.date.accessioned2026-01-15T09:12:16Z-
dc.date.available2026-01-15T09:12:16Z-
dc.date.issued2025-
dc.identifier.issn1820-6530en_US
dc.identifier.urihttps://scidar.kg.ac.rs/handle/123456789/22896-
dc.description.abstractIn silico clinical trials are set to transform medicine by enabling virtual testing and simulation, which streamline the development of medical devices and pharmaceuticals while reducing costs and duration. The SILICOFCM platform offers a innovative, multi-modular approach designed to optimize overall heart function and monitor the effectiveness of pharmacological treatments, aiming to decrease dependence on animal and human trials. It employs an integrated, multidisciplinary, and multiscale methodology to analyze patient-specific data, allowing the creation of personalized models that track disease progression. By combining data from various sources and scales with advanced computational techniques, SILICOFCM maps the flow of information from genetic mutations to organ dysfunction. The platform specifically targets hypertrophic (HCM) and dilated (DCM) cardiomyopathy through coupled macro- and microscale simulations utilizing finite element modeling of fluid-structure interaction (FSI) and molecular interactions within cardiac cells. This enables the simulation of left ventricular mechanics and the assessment of how different drugs influence electro-mechanical processes, including changes in calcium (Ca2+) handling and kinetic parameters. The overarching goal of the STRATIFYHF project is to develop and clinically validate an innovative AI-driven Decision Support System (DSS) to predict heart failure risk, support early diagnosis, and forecast disease progression—offering a paradigm shift in heart failure management across primary and secondary care. The DSS integrates patient-centered data from existing and emerging technologies, a digital patient library, and AI-based algorithms combined with computational modeling. Through workflows dedicated to improving heart performance and evaluating pharmacological effects, SILICOFCM and STRATIFYHF are paving new pathways to accelerate drug development and clinical testing.en_US
dc.language.isoen_USen_US
dc.relation.ispartofJournal of the Serbian Society for Computational Mechanicsen_US
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subjectcardiac cycleen_US
dc.subjectfinite element methoden_US
dc.titleHEART MODELING, INSILICO CLINICAL TRIALSen_US
dc.typearticleen_US
dc.identifier.doi10.24874/jsscm.2025.19.01.17en_US
Appears in Collections:Faculty of Engineering, Kragujevac

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