ArticleFrontiers in cardiovascular medicine2021
Using Innovative Machine Learning Methods to Screen and Identify Predictors of Congenital Heart Diseases.
Article in Frontiers in cardiovascular medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
16 citing papers in PubMed, 1 synthesis or guideline pooled it, 31 citations in OpenAlex.
- Effectiveness of machine learning for diagnosis and prognostic prediction of congenital heart disease: a systematic review and meta-analysis.BMC pediatrics · 2026Pooled it
- Explainable machine learning model for identifying key risk factors in congenital heart disease prediction using questionnaire data: a retrospective case-control study.BMC medical informatics and decision making · 2026Article
- Prioritization of patients at risk of heart attack using a novel full-objective ITARA based on Random Forest and Decision tree.Scientific reports · 2025Article
- Combining lipidomics and machine learning to identify lipid biomarkers for nonsyndromic cleft lip with palate.JCI insight · 2025Article
- The Artificial Intelligence-Enhanced Echocardiographic Detection of Congenital Heart Defects in the Fetus: A Mini-Review.Medicina (Kaunas, Lithuania) · 2025Review
- Article
- Machine learning detects symptomatic patients with carotid plaques based on 6-type calcium configuration classification on CT angiography.European radiology · 2024Article
- Machine Learning Detects Symptomatic Plaques in Patients With Carotid Atherosclerosis on CT Angiography.Circulation. Cardiovascular imaging · 2024Article
- A review of evaluation approaches for explainable AI with applications in cardiology.Artificial intelligence review · 2024Article
- [An interpretable machine learning-based prediction model for risk of death for patients with ischemic stroke in intensive care unit].Nan fang yi ke da xue xue bao = Journal of Southern Medical University · 2023Article
- A Cardiac Deep Learning Model (CDLM) to Predict and Identify the Risk Factor of Congenital Heart Disease.Diagnostics (Basel, Switzerland) · 2023Article
- Article
- Insights and perspectives into clinical biomarker discovery in pediatric heart failure and congenital heart disease-a narrative review.Cardiovascular diagnosis and therapy · 2023Review
- Clinlabomics: leveraging clinical laboratory data by data mining strategies.BMC bioinformatics · 2022Review
- Dietary Quality during Pregnancy and Congenital Heart Defects.Nutrients · 2022Article
- Building a predictive model to identify clinical indicators for COVID-19 using machine learning method.Medical & biological engineering & computing · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
15 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
PubMed holds no abstract for this paper.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.