Generating Synthetic Data for Machine Learning Models from the Pediatric Heart Network Fontan I Dataset

Background: The population of Fontan patients, patients born with a single functioning ventricle, is growing. There is a growing need to develop algorithms for this population that can predict health outcomes. Artificial inte... | Find, read and cite all the research you need on Tech Science Press

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Publication Details

Journal
Congenital Heart Disease
Published
2025-01-01
DOI
https://doi.org/10.32604/chd.2025.063991
Citations
2
Primary Topic
Energy Load and Power Forecasting
Type
article
Field-Weighted Citation Impact
1.46
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article

Generating Synthetic Data for Machine Learning Models from the Pediatric Heart Network Fontan I Dataset

John Valdovinos, Vatche Bahudian
2 citations
Congenital Heart Disease
Energy Load and Power Forecasting
1.46
article

Generating Synthetic Data for Machine Learning Models from the Pediatric Heart Network Fontan I Dataset

John Valdovinos, Vatche Bahudian
article en
2 citations

Abstract

Background: The population of Fontan patients, patients born with a single functioning ventricle, is growing. There is a growing need to develop algorithms for this population that can predict health outcomes. Artificial inte... | Find, read and cite all the research you need on Tech Science Press

Congenital Heart DiseaseVol. 20(1)
California State University, Northridge (US)
Openalex Percentile: Top 19%
Energy Load and Power Forecasting
1.46
DOIOpen Access PDFOpenAlex
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Generating Synthetic Data for Machine Learning Models from the Pediatric Heart Network Fontan I Dataset — John Valdovinos, Vatche Bahudian · Congenital Heart Disease (2025) | TGRS Research Map | TGRS