Multicenter validation of a machine learning model to predict intensive care unit readmission within 48 hours after discharge Article Swipe
Leerang Lim
,
Min Ja Kim
,
K. Cho
,
Dongjoon Yoo
,
Dayeon Sim
,
Ho Geol Ryu
,
Hyung‐Chul Lee
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.eclinm.2025.103112
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.1016/j.eclinm.2025.103112
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1016/j.eclinm.2025.103112
- OA Status
- gold
- Cited By
- 7
- References
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- Related Works
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- OpenAlex ID
- https://openalex.org/W4407555299
All OpenAlex metadata
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https://openalex.org/W4407555299Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1016/j.eclinm.2025.103112Digital Object Identifier
- Title
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Multicenter validation of a machine learning model to predict intensive care unit readmission within 48 hours after dischargeWork title
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-02-13Full publication date if available
- Authors
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Leerang Lim, Min Ja Kim, K. Cho, Dongjoon Yoo, Dayeon Sim, Ho Geol Ryu, Hyung‐Chul LeeList of authors in order
- Landing page
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https://doi.org/10.1016/j.eclinm.2025.103112Publisher landing page
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://doi.org/10.1016/j.eclinm.2025.103112Direct OA link when available
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Medicine, Intensive care unit, Emergency medicine, Multicenter study, Intensive care medicine, Medical emergency, Surgery, Randomized controlled trialTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
- Citations by year (recent)
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2025: 7Per-year citation counts (last 5 years)
- References (count)
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61Number of works referenced by this work
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10Other works algorithmically related by OpenAlex
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| primary_topic.score | 0.9983000159263611 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Machine Learning in Healthcare |
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| cited_by_count | 7 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 7 |
| locations_count | 4 |
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| best_oa_location.is_oa | True |
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| best_oa_location.source.issn | 2589-5370 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
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| best_oa_location.source.is_core | True |
| best_oa_location.source.is_in_doaj | True |
| best_oa_location.source.display_name | EClinicalMedicine |
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| best_oa_location.source.host_organization_name | Elsevier BV |
| best_oa_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| best_oa_location.source.host_organization_lineage_names | Elsevier BV |
| best_oa_location.license | |
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| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
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| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
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| primary_location.source.type | journal |
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| primary_location.source.issn_l | 2589-5370 |
| primary_location.source.is_core | True |
| primary_location.source.is_in_doaj | True |
| primary_location.source.display_name | EClinicalMedicine |
| primary_location.source.host_organization | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_name | Elsevier BV |
| primary_location.source.host_organization_lineage | https://openalex.org/P4310320990 |
| primary_location.source.host_organization_lineage_names | Elsevier BV |
| primary_location.license | |
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| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | eClinicalMedicine |
| primary_location.landing_page_url | https://doi.org/10.1016/j.eclinm.2025.103112 |
| publication_date | 2025-02-13 |
| publication_year | 2025 |
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| referenced_works_count | 61 |
| abstract_inverted_index | |
| cited_by_percentile_year.max | 99 |
| cited_by_percentile_year.min | 98 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 7 |
| citation_normalized_percentile.value | 0.99506794 |
| citation_normalized_percentile.is_in_top_1_percent | True |
| citation_normalized_percentile.is_in_top_10_percent | True |