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Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials

EBioMedicine(2021)10.1016/j.ebiom.2021.103697Source: DataRank Database

Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials is a research paper published in EBioMedicine (2021). On theSindex it has a DataRank of 0. It has been cited 60 times.

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Open Access60 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (12 grants)Impact (FWCI 5.70)OA: goldTopics (63)Linked Datasets (6)DataCite Reuse (6)IDs (PubMed, OpenAlex)SDGs (2)

FAIR Checklist

Context only (not used in score)

Findable (2/2)

Has DOI
Indexed in repositories

Accessible (1/2)

Open Access

Interoperable (2/2)

DataCite relations
Linked datasets

Reusable (0/3)

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Authors (6)

Alexandra B. Spicer ORCID,Kevin Delucchi ORCID,Daniel F. McAuley ORCID,Carolyn S. Calfee ORCID,Matthew M. Churpek ORCID

Live enrichment

PubMed:34861492 OpenAlex:https://openalex.org/W3215954095

U.S. Department of Defense

Grant: W81XWH-21-1-0009

U.S. Department of Defense

Grant: R21 AG068720

U.S. Department of Defense

Grant: R01 GM123193

U.S. Department of Defense

Grant: R35 HL140026

U.S. Department of Defense

Grant: R35 GM142992

U.S. Department of Defense

Grant: R01 DA051464

National Institutes of Health

Grant: 5R21AG068720-02

Characterization and Identification of Markers of Clinical Momentum in the Care of Older Adults with Advanced Dementia

National Institutes of Health

Grant: 5R35HL140026-03

Precision Medicine in the Acute Respiratory Distress Syndrome

Wellcome Trust

Grant: unidentified

unidentified

National Institutes of Health

Grant: 1R35GM142992-01

Precision Medicine in Sepsis with Critical Illness

National Institutes of Health

Grant: 3R01DA051464-02S1

Building a Substance Use Data Commons for Public Health Informatics

National Institutes of Health

Grant: 1R01GM123193-01

Sepsis Early Prediction and Subphenotype Illumination Study (SEPSIS)

FWCI

5.70

Citation Percentile

1.0%

Influential Citations

Citation Trend

2021

2022

2023

2024

2025

2026

goldLicense: cc-by

journalhttp://www.thelancet.com/article/S2352396421004916/pdf

GOLDhttp://www.thelancet.com/article/S2352396421004916/pdf

publisherhttp://www.thelancet.com/article/S2352396421004916/pdf

publisherhttps://api.elsevier.com/content/article/PII:S2352396421004916?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2352396421004916?httpAccept=text/plain

Fields of Study

Sepsis Diagnosis and TreatmentRespiratory Support and MechanismsAdvanced Causal Inference TechniquesMedicineComputer Science03 medical and health sciences0302 clinical medicineHumansAlgorithmsBayes TheoremCluster AnalysisRandomized Controlled Trials as TopicRespiratory Distress SyndromeSupervised Machine LearningTreatment OutcomeUnsupervised Machine Learning

MeSH Terms

Supervised Machine LearningUnsupervised Machine LearningAlgorithmsBayes TheoremHumansRespiratory Distress SyndromeCluster AnalysisRandomized Controlled Trials as TopicTreatment Outcome

Keywords

Random forestRecursive partitioningMachine learningCluster analysisComputer scienceArtificial intelligenceAlgorithmRandomized controlled trialMedicineInternal medicineMedicine (General)Research paperEpidemiologyClinical SciencesClinical Trials and Supportive Activities610ClusteringRare DiseasesR5-920Clinical ResearchHumansLungRandomized Controlled Trials as TopicRCTsRespiratory Distress SyndromeBiomedical and Clinical SciencesLCAR006Bayes TheoremHeterogeneity of treatment effectGood Health and Well BeingTreatment OutcomePublic Health and Health ServicesARDSSupervised Machine LearningAlgorithmsUnsupervised Machine Learning

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Good health and well-being

Additional file 1 of One-year patient outcomes based on lung morphology in acute respiratory distress syndrome: secondary analysis of LIVE trial

10.6084/m9.figshare.20003867.v1figshare

Additional file 1 of One-year patient outcomes based on lung morphology in acute respiratory distress syndrome: secondary analysis of LIVE trial

10.6084/m9.figshare.20003867figshare

Additional file 2 of Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

10.6084/m9.figshare.23488834figshare

Additional file 1 of Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

10.6084/m9.figshare.23488831.v1figshare

Additional file 2 of Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

10.6084/m9.figshare.23488834.v1figshare

Additional file 1 of Factors associated with circulatory death after out-of-hospital cardiac arrest: a population-based cluster analysis

10.6084/m9.figshare.23488831figshare