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

A Machine-Learning Framework to Identify Distinct Phenotypes of Aortic Stenosis Severity

JACC. Cardiovascular imaging(2021)10.1016/j.jcmg.2021.03.020Source: DataRank Database

A Machine-Learning Framework to Identify Distinct Phenotypes of Aortic Stenosis Severity is a research paper published in JACC. Cardiovascular imaging (2021). On theSindex it has a DataRank of 0.675. It has been cited 89 times.

N/A

0.675DataRank · unranked

Scored on demand from live citation data

Open Access89 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 (19 grants)Impact (FWCI 8.65)OA: hybridTopics (40)IDs (PubMed, PMC, OpenAlex)SDGs (3)

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.

DataRank Breakdown

Base Score 100%Citation Network 0%

Base Score Contribution

0.675

From this paper's citation signal

Citation Network Contribution

Citation network not refreshed for this result

This paper's DataRank is currently driven only by its base citation score. Citation network data was not refreshed for this result.

Learn more about DataRank methodology →

Authors (40)

Sirish Shrestha ORCID,Nobuyuki Kagiyama ORCID,Yasmin S. Hamirani ORCID,Hemant Kulkarni ORCID,Naveena Yanamala ORCID

Live enrichment

PubMed:34023273 PMC:PMC8434951 OpenAlex:https://openalex.org/W3161997410

Wellcome Trust

Grant: 15/JTA

Wellcome Trust

Grant: FS/14/78/31020

Wellcome Trust

Grant: WT103782AIA

British Heart Foundation

Grant: CH/09/002

British Heart Foundation

Grant: RE/18/5/34216

British Heart Foundation

Grant: RG/16/10/32375

National Institutes of Health

Grant: 5U54GM104942-04

West Virginia Clinical and Translational Science Institute: Improving Health through Partnerships and Transformative Research

National Science Foundation

Grant: 1920920

RII Track 2 FEC: Multi-Scale Integrative Approach to Digital Health: Collaborative Research and Education in Smart Health in West Virginia and Arkansas

British Heart Foundation

Grant: CH/09/002/26360

British Heart Foundation

Grant: FS/16/19/31982

NIGMS NIH HHS

Grant: U54 GM104942

Canadian Institutes of Health Research

Grant: unidentified

unidentified

Wellcome Trust

Grant: 103782

Identification and Prediction of Coronary Artery Plaque Rupture Using 18F-Fluoride Positron Emission Tomography.

National Institute of General Medical Sciences

Canadian Institutes of Health Research

Fonds de Recherche du Québec - Santé

NSF

Wellcome Trust

FWCI

8.65

Citation Percentile

1.0%

Citation Trend

2021

2022

2023

2024

2025

2026

hybridLicense: other-oa

journalhttps://www.sciencedirect.com/science/article/pii/S1936878X21002862/pdf

publisherhttps://www.sciencedirect.com/science/article/pii/S1936878X21002862/pdf

publisherhttps://api.elsevier.com/content/article/PII:S1936878X21002862?httpAccept=text/xml

publisherhttps://api.elsevier.com/content/article/PII:S1936878X21002862?httpAccept=text/plain

journalhttps://doi.org/10.1016/j.jcmg.2021.03.020

Fields of Study

Cardiac Valve Diseases and TreatmentsCardiovascular Function and Risk FactorsCardiac Imaging and Diagnostics03 medical and health sciences0302 clinical medicineAortic ValveAortic Valve StenosisHeart Valve Prosthesis ImplantationHumansMachine LearningPhenotypePredictive Value of TestsSeverity of Illness Index

MeSH Terms

Machine LearningAortic ValveAortic Valve StenosisHumansPhenotypePredictive Value of TestsSeverity of Illness IndexHeart Valve Prosthesis Implantation

Keywords

MedicineInternal medicineCohortCardiologyMagnetic resonance imagingStenosisSeverity of illnessAortic valve replacementRadiologyAortic StenosisMachine LearningTopological Data AnalysisHeart Valve Prosthesis ImplantationPhenotypePredictive Value of TestsAortic ValveHumansAortic Valve StenosisSeverity of Illness Index

Sustainable Development Goals

SDG 3: 3. Good healthSDG 0: Peace, Justice and strong institutionsSDG 0: Reduced inequalities