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Improving 1-year mortality prediction in ACS patients using machine learning

European Heart Journal Acute Cardiovascular Care(2021)10.1093/ehjacc/zuab030Source: DataRank Database

Improving 1-year mortality prediction in ACS patients using machine learning is a research paper published in European Heart Journal Acute Cardiovascular Care (2021). On theSindex it has a DataRank of 1.0. It has been cited 20 times, with 17 citing works in its 1-hop citation network.

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1.0DataRank · unranked

Scored on demand from live citation data

Deposits data Open Access20 citations · 17 citing works in its network

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Linked data & code

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Data availability

Repositories this paper deposited data in (declared in PubMed).

ClinicalTrials.govNCT01000701

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 (23 grants)Impact (FWCI 1.74)OA: bronzeTopics (38)IDs (PubMed, PMC, OpenAlex)Annotations (1)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)

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DataRank Breakdown

Base Score 46%Citation Network 54%

Base Score Contribution

0.457

From this paper's citation signal

Citation Network Contribution

0.545

From 13 citing papers with measurable signal

Learn more about DataRank methodology →

Top 5 citers driving the network score

Ranked by each citer's contribution to N(p) — log1p(C_q) divided by its reference count — out of 17 citers.

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Prediction of 3-year all-cause and cardiovascular cause mortality in a prospective percutaneous coronary intervention registry: Machine learning model outperforms conventional clinical risk scores
Atherosclerosis202229 citations33 referencesContributes 0.103
Artificial Intelligence of Arterial Doppler Waveforms to Predict Major Adverse Outcomes Among Patients Evaluated for Peripheral Artery Disease
Journal of the American Heart Association202426 citations40 referencesContributes 0.082
Using machine learning to predict adverse events in acute coronary syndrome: A retrospective study
Clinical Cardiology202314 citations35 referencesContributes 0.077
Challenges and promises of machine learning-based risk prediction modelling in cardiovascular disease
European Heart Journal Acute Cardiovascular Care20213 citations20 referencesContributes 0.069

Authors (19)

Alessandro Candreva ORCID,Rebekka Burkholz,Roland Klingenberg ORCID,Lorenz Räber ORCID,Dik Heg ORCID

Live enrichment

PubMed:34015112 PMC:PMC8557454 OpenAlex:https://openalex.org/W3163871649

Swiss National Science Foundation

Grant: 33CM30-124112

Swiss National Science Foundation

Grant: 32473B_163271

SNSF

Grant: 310030-146923

SNSF

Grant: 310030-165990

National Institutes of Health

Grant: HL103866

National Institutes of Health

Grant: 1P01 HL147823

Swiss National Science Foundation

Grant: 163271

Long-term Benefit of the Multi-Center, Multi-Dimensional Secondary Prevention Program in Patients With Acute Coronary Syndromes

Swiss National Science Foundation

Grant: 146923

Swiss National Science Foundation

Grant: 165990

Swiss National Science Foundation

Grant: 124112

Inflammation and acute coronary syndrome (ACS) - novel strategies for prevention and clinical management

NHLBI NIH HHS

Grant: P01 HL147823

NHLBI NIH HHS

Grant: R01 HL103866

Swiss National Science Foundation

Grant: 310030

Swiss National Science Foundation

Grant: 32473

Biological control of soil-borne diseases by Pseudomonas fluorescens: mechanisms and regulatory aspects

National Institutes of Health

Grant: 5P01HL147823-03

Gut Microbiota and Cardiometabolic Diseases

National Institutes of Health

Grant: 5R01HL103866-03

Gut flora metabolism of dietary phosphatidylcholine and cardiovascular disease

Max Planck ETH Center for Learning Systems

Zurich Heart House-Foundation of Cardiovascular Research

AstraZeneca

Leducq Foundation

Swiss Personalized Health Network

Zurich Heart House—Foundation of Cardiovascular Research

Personal Health and Related Technologies

FWCI

1.74

Citation Percentile

0.9%

Citation Trend

2021

2022

2023

2024

2025

bronzeLicense: OUP Standard Publication Reuse

journalhttps://academic.oup.com/ehjacc/article-pdf/10/8/855/40935740/zuab030.pdf

BRONZEhttps://academic.oup.com/ehjacc/article-pdf/10/8/855/40935740/zuab030.pdf

publisherhttps://academic.oup.com/ehjacc/article-pdf/10/8/855/40935740/zuab030.pdf

publisherhttp://academic.oup.com/ehjacc/article-pdf/10/8/855/40935740/zuab030.pdf

journalhttps://doi.org/10.1093/ehjacc/zuab030

Fields of Study

Machine Learning in HealthcareArtificial Intelligence in HealthcareSepsis Diagnosis and TreatmentMedicineComputer Science03 medical and health sciences0302 clinical medicine

MeSH Terms

Machine LearningHumansPrognosisRisk FactorsStroke VolumeVentricular Function, LeftRisk AssessmentAcute Coronary Syndrome

Keywords

MedicineInternal medicineIntensive care medicineEmergency medicineCardiologyAgeAcute coronary syndromesNT-proBNPMachine LearningGrace 2.0 ScoreAcute Coronary Syndrome / diagnosis610 Medicine & healthStroke VolumePrognosisRisk AssessmentVentricular Function, LeftRisk Factors540 Chemistry61610209 Clinic for CardiologyHumansAcute Coronary Syndrome10038 Institute of Clinical Chemistry

Sustainable Development Goals

SDG 2: 2. Zero hungerSDG 3: 3. Good healthSDG 0: Good health and well-being

Related Papers (1)

Leveraging Machine Learning and Artificial Intelligence to Improve Peripheral Artery Disease Detection, Treatment, and Outcomes

Circulation Research(2021)

co-cited

10.1161/circresaha.121.318224

Improving 1-year mortality prediction in ACS patients using machine learning

FAIR Checklist

DataRank Breakdown

Top 5 citers driving the network score

Authors (19)

Funding (23 grants)

Impact

Open Access

Topics

Annotations (Europe PMC)

Related Papers (1)