Pilot corpus: NIH-funded biomedical datasets. Any DOI can be scored on demand — network effects sharpen as coverage grows.

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness

EBioMedicine(2023)10.1016/j.ebiom.2023.104938Source: DataRank Database

Machine learning-driven identification of the gene-expression signature associated with a persistent multiple organ dysfunction trajectory in critical illness is a research paper published in EBioMedicine (2023). On theSindex it has a DataRank of 0. It has been cited 23 times.

N/A

0DataRank · unranked

Scored on demand from live citation data

Open Access23 citations

Download PDF

Cite:

DataRank reads this dataset's downstream impact straight off the citation graph — no black box, no proprietary weighting. How is this computed?

›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (3 grants)Impact (FWCI 3.87)OA: goldTopics (35)IDs (PubMed, OpenAlex)SDGs (1)

FAIR Checklist

Context only (not used in score)

Findable (1/2)

Has DOI

Accessible (1/2)

Open Access

Interoperable (0/2)

Reusable (0/3)

FAIR checklist signals are shown for context only and do not affect DataRank scoring.

Run a calibrated FAIR evaluation for this paper →

We only score data papers we can read in full — never from an abstract alone.

Authors (25)

Shayantan Banerjee ORCID,Andrew J. Lautz ORCID,Matthew N. Alder ORCID,Brian M. Varisco ORCID,Hector R. Wong ORCID

Live enrichment

PubMed:38142638 OpenAlex:https://openalex.org/W4390151009

NIGMS

Grant: R01GM139967

NIGMS

Grant: R21GM151703

NIGMS

Grant: R35GM126943

FWCI

3.87

Citation Percentile

0.9%

Citation Trend

2024

2025

2026

goldLicense: cc-by-nc-nd

journalhttp://www.thelancet.com/article/S2352396423005042/pdf

publisherhttp://www.thelancet.com/article/S2352396423005042/pdf

publisherhttps://api.elsevier.com/content/article/PII:S2352396423005042?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S2352396423005042?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.ebiom.2023.104938

Fields of Study

Sepsis Diagnosis and TreatmentImmune Response and InflammationInflammation biomarkers and pathwaysHumansChildMultiple Organ FailureCritical IllnessReproducibility of ResultsSepsisMachine Learning

MeSH Terms

Machine LearningChildHumansMultiple Organ FailureReproducibility of ResultsCritical IllnessSepsis

Keywords

Multiple organ dysfunction syndromeOrgan dysfunctionSepsisMedicineSeptic shockGene signatureTest setMachine learningGeneBioinformaticsBiologyInternal medicineComputer scienceGene expressionGeneticsCritical illnessPrecision medicineSupervised machine learning

Sustainable Development Goals

SDG 0: Good health and well-being