The potential of the Medical Digital Twin in diabetes management: a review

Chu, Yiqi; Li, Shanhong; Tang, Jie; Wu, Huiqun

doi:10.3389/fmed.2023.1178912

Cited by 8 publications

(2 citation statements)

References 37 publications

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“…Recent studies have introduced various digital twin systems, covering areas such as hospital management 8 , remote monitoring 9 , and diagnosing and treating various conditions 39 , 40 . Nevertheless, these systems were not included in this review due to the lack of detailed descriptions at the population health level, which constrains the broader application of this emerging technology.…”

Section: Discussionmentioning

confidence: 99%

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

Shen,

Chen,

Ding

2024

npj Digit. Med.

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Digital twins represent a promising technology within the domain of precision healthcare, offering significant prospects for individualized medical interventions. Existing systematic reviews, however, mainly focus on the technological dimensions of digital twins, with a limited exploration of their impact on health-related outcomes. Therefore, this systematic review aims to explore the efficacy of digital twins in improving precision healthcare at the population level. The literature search for this study encompassed PubMed, Embase, Web of Science, Cochrane Library, CINAHL, SinoMed, CNKI, and Wanfang Database to retrieve potentially relevant records. Patient health-related outcomes were synthesized employing quantitative content analysis, whereas the Joanna Briggs Institute (JBI) scales were used to evaluate the quality and potential bias inherent in each selected study. Following established inclusion and exclusion criteria, 12 studies were screened from an initial 1321 records for further analysis. These studies included patients with various conditions, including cancers, type 2 diabetes, multiple sclerosis, heart failure, qi deficiency, post-hepatectomy liver failure, and dental issues. The review coded three types of interventions: personalized health management, precision individual therapy effects, and predicting individual risk, leading to a total of 45 outcomes being measured. The collective effectiveness of these outcomes at the population level was calculated at 80% (36 out of 45). No studies exhibited unacceptable differences in quality. Overall, employing digital twins in precision health demonstrates practical advantages, warranting its expanded use to facilitate the transition from the development phase to broad application.PROSPERO registry: CRD42024507256.

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Section: Discussionmentioning

confidence: 99%

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

Shen,

Chen,

Ding

2024

npj Digit. Med.

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“…A digital twin is a virtual replica of a physical entity capable of modeling and simulating its behavior and environmental interactions [4]. Applied successfully in industries like aerospace and manufacturing [5], digital twins now open new possibilities for personalized medicine and precision healthcare [4]. This paper explores digital twins specifically for diabetes management, focusing on the aspects of condition prediction and control.…”

Section: Introductionmentioning

confidence: 99%

Personalized Diabetes Management with Digital Twins: A Patient-Centric Knowledge Graph Approach

Sarani Rad,

Hendawi,

Yang

et al. 2024

JPM

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Diabetes management requires constant monitoring and individualized adjustments. This study proposes a novel approach that leverages digital twins and personal health knowledge graphs (PHKGs) to revolutionize diabetes care. Our key contribution lies in developing a real-time, patient-centric digital twin framework built on PHKGs. This framework integrates data from diverse sources, adhering to HL7 standards and enabling seamless information access and exchange while ensuring high levels of accuracy in data representation and health insights. PHKGs offer a flexible and efficient format that supports various applications. As new knowledge about the patient becomes available, the PHKG can be easily extended to incorporate it, enhancing the precision and accuracy of the care provided. This dynamic approach fosters continuous improvement and facilitates the development of new applications. As a proof of concept, we have demonstrated the versatility of our digital twins by applying it to different use cases in diabetes management. These include predicting glucose levels, optimizing insulin dosage, providing personalized lifestyle recommendations, and visualizing health data. By enabling real-time, patient-specific care, this research paves the way for more precise and personalized healthcare interventions, potentially improving long-term diabetes management outcomes.

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A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review

Pellegrino,

Gervasi,

Angelelli

et al. 2024

Inf Syst Front

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Digital Twin (DT) technology monitors, simulates, optimizes, models, and predicts the behavior of physical entities. Healthcare is a significant domain where a DT can be functional for multiple purposes. However, these diverse uses of DTs need a clear understanding of both general and specific aspects that can affect their adoption and integration. This paper is a meta-review that leads to the development of a conceptual framework designed to support the high-level evaluation of DTs in healthcare. Using the PRISMA methodology, the meta-review synthesizes insights from 20 selected reviews out of 1,075 studies. Based on this comprehensive analysis, we extract the functional, technological, and operational aspects that characterize DTs in healthcare. Additionally, we examine the structural (e.g., hierarchical) relationships among these aspects to address the various complexity scales in digital health. The resulting framework can promote the effective design and implementation of DTs, offering a structured approach for their assessment.

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The potential of the Medical Digital Twin in diabetes management: a review

Cited by 8 publications

References 37 publications

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

The effectiveness of digital twins in promoting precision health across the entire population: a systematic review

Personalized Diabetes Management with Digital Twins: A Patient-Centric Knowledge Graph Approach

A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review

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