Data Management Plan I

Abstract

The COMFORTage project aims to leverage advanced Artificial Intelligence (AI) tools and a suite of specialized applications to enhance the study of dementia and frailty among elderly populations across multiple pilot clinical and research sites. The primary objective is to utilize data-driven insights to improve diagnostic accuracy, treatment efficacy, and overall patient care. By integrating AI-driven analytics with clinical data, the project seeks to identify patterns and predictors of dementia and frailty, thereby enabling early intervention and personalized treatment plans. This data management plan outlines the strategic framework for collecting, storing, processing, and securing large amounts of patient data while ensuring compliance with ethical standards and regulatory requirements. Data will be gathered from various clinical and research sites, ensuring a diverse and representative sample of the elderly population. The plan includes protocols for data anonymization, secure storage, and controlled access to safeguard patient confidentiality. Advanced AI algorithms will be employed to analyse the data, providing real-time insights and predictive models that can support either patient observation or clinical decision-making. Collaboration between sites will be facilitated through a centralized data repository, allowing for seamless data sharing and integration. Regular audits and reviews will be conducted to maintain data integrity and quality. The COMFORTage project is committed to adhering to the highest standards of data management, with the ultimate goal of contributing to the academic body of knowledge and advancing our understanding of dementia and frailty, thereby informing future research and clinical practices.

Ähnliche Arbeiten