A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review Article Swipe
Giulia Pellegrino
,
Massimiliano Gervasi
,
Mario Angelelli
,
Angelo Corallo
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s10796-024-10536-4
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.1007/s10796-024-10536-4
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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Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1007/s10796-024-10536-4
- OA Status
- hybrid
- Cited By
- 23
- References
- 101
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4402489852
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4402489852Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1007/s10796-024-10536-4Digital Object Identifier
- Title
-
A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-ReviewWork title
- Type
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articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2024Year of publication
- Publication date
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2024-09-12Full publication date if available
- Authors
-
Giulia Pellegrino, Massimiliano Gervasi, Mario Angelelli, Angelo CoralloList of authors in order
- Landing page
-
https://doi.org/10.1007/s10796-024-10536-4Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
hybridOpen access status per OpenAlex
- OA URL
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https://doi.org/10.1007/s10796-024-10536-4Direct OA link when available
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Health care, Computer science, Conceptual framework, Systematic review, Data science, Knowledge management, MEDLINE, Sociology, Political science, Social science, LawTop concepts (fields/topics) attached by OpenAlex
- Cited by
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23Total citation count in OpenAlex
- Citations by year (recent)
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2025: 22, 2024: 1Per-year citation counts (last 5 years)
- References (count)
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101Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| abstract_inverted_index.optimizes, | 7 |
| abstract_inverted_index.simulates, | 6 |
| abstract_inverted_index.structural | 115 |
| abstract_inverted_index.structured | 145 |
| abstract_inverted_index.technology | 4 |
| abstract_inverted_index.assessment. | 149 |
| abstract_inverted_index.development | 62 |
| abstract_inverted_index.functional, | 101 |
| abstract_inverted_index.healthcare. | 76, 110 |
| abstract_inverted_index.meta-review | 57, 82 |
| abstract_inverted_index.operational | 104 |
| abstract_inverted_index.significant | 19 |
| abstract_inverted_index.synthesizes | 83 |
| abstract_inverted_index.characterize | 107 |
| abstract_inverted_index.integration. | 52 |
| abstract_inverted_index.methodology, | 80 |
| abstract_inverted_index.Additionally, | 111 |
| abstract_inverted_index.comprehensive | 96 |
| abstract_inverted_index.hierarchical) | 117 |
| abstract_inverted_index.relationships | 118 |
| abstract_inverted_index.understanding | 39 |
| abstract_inverted_index.implementation | 140 |
| abstract_inverted_index.technological, | 102 |
| cited_by_percentile_year.max | 100 |
| cited_by_percentile_year.min | 90 |
| countries_distinct_count | 0 |
| institutions_distinct_count | 4 |
| citation_normalized_percentile.value | 0.98728067 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |