Advancing Online Health Community Engagement through Digital Twin Technology: A Biotechnological Approach to Information Fusion

Abstract

The rapid proliferation of health-related information within online health communities presents both challenges and opportunities in terms of ensuring the accuracy and utility of the information provided. The primary goal of information fusion in these communities is to reconcile user demand for precise health education with the vast array of available online health data. This paper explores the innovative integration of digital twin technology to enhance the utility of online health community information by seamlessly blending it with professional medical knowledge. This integration fosters a sophisticated support system for diagnostic and treatment decision-making, reflecting the cutting-edge trends in online health knowledge services. Furthermore, the growing consumer demand for advanced online health community knowledge services presents significant opportunities for the development of medical informatics that align with ongoing reforms and trends in healthcare. This study outlines a comprehensive approach involving theoretical models, implementation modes, practical applications, and optimization measures. It leverages an interdisciplinary theoretical framework to apply digital twin technology, constructing a multi-level integration model that combines online health community information with intelligent internet technology in a medical health service management system. This integration lays a crucial groundwork for the future development and innovation of online health community services, ensuring that these platforms can provide not only information but also actionable insights and decision-support tools in healthcare. By utilizing digital twin technology, this approach aims to create a more dynamic, responsive, and effective online health environment, enhancing the quality of information and service delivery to meet contemporary healthcare demands.