CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization

Author:

Carbonaro Antonella,Marfoglia Alberto,Nardini Filippo,Mellone Sabato

Abstract

Healthcare has always been a strategic domain in which innovative technologies can be applied to increase the effectiveness of services and patient care quality. Recent advancements have been made in the adoption of Digital Twins (DTs) and Personal Knowledge Graphs (PKGs) in this field. Despite this, their introduction has been hindered by the complex nature of the context itself which leads to many challenges both technical and organizational. In this article, we reviewed the literature about these technologies and their integrations, identifying the most critical requirements for clinical platforms. These latter have been used to design CONNECTED (COmpreheNsive and staNdardized hEalth-Care plaTforms to collEct and harmonize clinical Data), a conceptual framework aimed at defining guidelines to overcome the crucial issues related to the development of healthcare applications. It is structured in a multi-layer shape, in which heterogeneous data sources are first integrated, then standardized, and finally used to realize general-purpose DTs of patients backed by PKGs and accessible through dedicated APIs. These DTs will be the foundation on which smart applications can be built.

Publisher

Frontiers Media SA

Subject

Health Informatics,Medicine (miscellaneous),Biomedical Engineering,Computer Science Applications

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Corrigendum: CONNECTED: leveraging digital twins and personal knowledge graphs in healthcare digitalization;Frontiers in Digital Health;2024-05-23

2. Representation of Machine Learning Models to Enhance Simulation Capabilities Within Digital Twins in Personalized Healthcare;2024 IEEE International Conference on Pervasive Computing and Communications Workshops and other Affiliated Events (PerCom Workshops);2024-03-11

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