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Customizable Rule-Based System for Enhanced Clinical Decision-Making in Dementia Risk Reduction.

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Název: Customizable Rule-Based System for Enhanced Clinical Decision-Making in Dementia Risk Reduction.
Autoři: PLUCH, Laura, HILBERGER, Hannes, BÖDENLER, Markus, UNTERSTEINER, Helena, HANKE, Sten
Zdroj: Studies in Health Technology & Informatics; 2025, Vol. 327, p73-77, 5p
Abstrakt: This study presents the development of a customizable rule-based engine, integrated into the LETHE Clinical Trial Management System (CTMS), designed to enhance clinical decision-making in a multidomain intervention for dementia risk reduction. The rule engine allows health professionals to create and personalize rules based on patient-specific profiles and evolving clinical knowledge, enabling more precise interventions. The system was developed through a collaborative approach with one health professional and employs a JSON based rules engine for flexible rule creation and implementation. Its application in the LETHE project, a randomized control trial involving 156 participants across multiple centers, demonstrates the potential of tailored digital interventions in improving clinical outcomes. Future enhancements will focus on broadening the system’s usability and automating patient-specific tasks to streamline care. [ABSTRACT FROM AUTHOR]
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Databáze: Complementary Index
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Abstrakt:This study presents the development of a customizable rule-based engine, integrated into the LETHE Clinical Trial Management System (CTMS), designed to enhance clinical decision-making in a multidomain intervention for dementia risk reduction. The rule engine allows health professionals to create and personalize rules based on patient-specific profiles and evolving clinical knowledge, enabling more precise interventions. The system was developed through a collaborative approach with one health professional and employs a JSON based rules engine for flexible rule creation and implementation. Its application in the LETHE project, a randomized control trial involving 156 participants across multiple centers, demonstrates the potential of tailored digital interventions in improving clinical outcomes. Future enhancements will focus on broadening the system’s usability and automating patient-specific tasks to streamline care. [ABSTRACT FROM AUTHOR]
ISSN:09269630
DOI:10.3233/SHTI250276