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Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches

JMIR Cardio(2023)10.2196/45352Source: DataRank Database

Prediction of Outcomes After Heart Transplantation in Pediatric Patients Using National Registry Data: Evaluation of Machine Learning Approaches is a research paper published in JMIR Cardio (2023). On theSindex it has a DataRank of 0. It has been cited 14 times.

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0DataRank · unranked

Scored on demand from live citation data

Open Access14 citations

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›Methodology & internals

datarank_citation_only_1hop_v6· scope data_onlyMethodology

Pipeline:MetadataData-paper checkEnrichmentCitation networkScoring

Enrichment:Funding (4 grants)Impact (FWCI 3.87)OA: goldTopics (32)IDs (PubMed, PMC, 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)

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Authors (7)

Shubo Tian ORCID,Aiwen Xing ORCID,Dana Hughes ORCID,Dipankar Gupta ORCID,Xiaoyu Wang ORCID

Live enrichment

PubMed:37338974 PMC:PMC10334720 OpenAlex:https://openalex.org/W4381309868

NLM NIH HHS

Grant: R21 LM013911

NCATS NIH HHS

Grant: UL1 TR001427

National Institutes of Health

Grant: 1R21LM013911-01

Prediction of Health Outcomes and Adverse Events in Pediatric Organ Transplantation in Florida

National Institutes of Health

Grant: 5UL1TR001427-08

Together: Transforming and Translating Discovery to Improve Health

FWCI

3.87

Citation Percentile

0.9%

Citation Trend

2023

2024

2025

2026

goldLicense: cc-by

journalhttps://jmir.org/api/download?alt_name=cardio_v7i1e45352_app1.pdf&filename=21a351e0c1ce57ca2d0b0203eb4b1bd7.pdf

publisherhttps://jmir.org/api/download?alt_name=cardio_v7i1e45352_app1.pdf&filename=21a351e0c1ce57ca2d0b0203eb4b1bd7.pdf

publisherhttps://cardio.jmir.org/2023/1/e45352

journalhttps://doi.org/10.2196/45352

repositoryhttps://pubmed.ncbi.nlm.nih.gov/37338974

Fields of Study

Transplantation: Methods and OutcomesRenal Transplantation Outcomes and TreatmentsOrgan Transplantation Techniques and Outcomes0202 electrical engineering, electronic engineering, information engineering02 engineering and technology

Keywords

Gradient boostingAdaBoostMachine learningRandom forestArtificial intelligenceMedicineReceiver operating characteristicSoftmax functionTransplantationMultilayer perceptronLogistic regressionStochastic gradient descentHeart transplantationSupport vector machineComputer scienceInternal medicineArtificial neural networkMortalityOrgan transplantationPediatricsUnited Network For Organ SharingOutcome PredictionOrgan RejectionExplainable Artificial IntelligenceOriginal PaperRC666-701Diseases of the circulatory (Cardiovascular) system

Sustainable Development Goals

SDG 0: Good health and well-being