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Neural Network Predicts Need for Red Blood Cell Transfusion for Patients with Acute Gastrointestinal Bleeding Admitted to the Intensive Care Unit

medRxiv(2020)10.1101/2020.05.19.20096743Source: DataRank Database

Neural Network Predicts Need for Red Blood Cell Transfusion for Patients with Acute Gastrointestinal Bleeding Admitted to the Intensive Care Unit is a research paper published in medRxiv (2020). On theSindex it has a DataRank of 0.484. It has been cited 6 times, with 4 citing works in its 1-hop citation network.

N/A

0.484DataRank · unranked

Scored on demand from live citation data

Open Access6 citations · 4 citing works in its network

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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 (1 grants)Topics (2)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)

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DataRank Breakdown

Base Score 60%Citation Network 40%

Base Score Contribution

0.292

From this paper's citation signal

Citation Network Contribution

0.192

From 3 citing papers with measurable signal

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Top 4 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 4 citers.

Predicting blood transfusion demand in intensive care patients after surgery by comparative analysis of temporally extended data selection
BMC Medical Informatics and Decision Making20244 citations20 referencesContributes 0.080
Accelerating Prediction of Malignant Cerebral Edema After Ischemic Stroke with Automated Image Analysis and Explainable Neural Networks
Neurocritical Care202130 citations43 referencesContributes 0.080
From demand forecasting to inventory ordering decisions for red blood cells through integrating machine learning, statistical modeling, and inventory optimization
Transfusion202141 citations57 referencesContributes 0.066
Analysis of the diagnostic utility of Glasgow-Blatcford Score, Rockall Score, AIMS65 Score, BUN-to-albumin ratio and BUN-to-creatinine ratio for predicting the need for transfusion in upper gastrointestinal bleeding
Medical Science and Discovery20230 citations35 referencesContributes 0.000

Authors (7)

Egbert Castro ORCID,Jessie Huang ORCID,J. Kenneth Tay ORCID,Michael Simonov ORCID,Loren Laine ORCID

Live enrichment

National Institutes of Health

Grant: 5T32DK007017-28

Training Program in Investigative Gastroenterology

Fields of Study

0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Sustainable Development Goals

SDG 3: 3. Good health