On the public citation graph

A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population

https://doi.org/10.1371/journal.pone.0237321
0 signed · 77 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/14651858.cd011188.pub2openalex-snapshot
Corticosteroids for the treatment of Kawasaki disease in children
inferredcites →https://doi.org/10.1002/14651858.cd011188.pub3openalex-snapshot
Corticosteroids for the treatment of Kawasaki disease in children
inferredcites →https://doi.org/10.1007/s00246-002-0216-2openalex-snapshot
Immunoglobulin Failure and Retreatment in Kawasaki Disease
inferredcites →https://doi.org/10.1007/s00246-012-0589-9openalex-snapshot
Steroid Pulse Therapy for Children With Intravenous Immunoglobulin Therapy–Resistant Kawasaki Disease: A Prospective Study
inferredcites →https://doi.org/10.1007/s00431-018-3297-5openalex-snapshot
Inability of Asian risk scoring systems to predict intravenous immunoglobulin resistance and coronary lesions in Kawasaki disease in an Italian cohort
inferredcites →https://doi.org/10.1016/j.amjcard.2016.11.055openalex-snapshot
Usefulness of Calcium Scoring as a Screening Examination in Patients With a History of Kawasaki Disease
inferredcites →https://doi.org/10.1016/j.echo.2016.03.017openalex-snapshot
A New Z Score Curve of the Coronary Arterial Internal Diameter Using the Lambda-Mu-Sigma Method in a Pediatric Population
inferredcites →https://doi.org/10.1016/j.jfma.2015.03.012openalex-snapshot
Risk factors and derived formosa score for intravenous immunoglobulin unresponsiveness in Taiwanese children with Kawasaki disease
inferredcites →https://doi.org/10.1016/j.jpeds.2006.03.050openalex-snapshot
Prediction of resistance to intravenous immunoglobulin treatment in patients with Kawasaki disease
inferredcites →https://doi.org/10.1016/j.jpeds.2010.10.012openalex-snapshot
Infliximab for Intravenous Immunoglobulin Resistance in Kawasaki Disease: A Retrospective Study
inferredcites →https://doi.org/10.1016/j.jpeds.2010.10.031openalex-snapshot
Evaluation of Kawasaki Disease Risk-Scoring Systems for Intravenous Immunoglobulin Resistance
inferredcites →https://doi.org/10.1016/j.jpeds.2016.07.035openalex-snapshot
The Combined Usefulness of the Neutrophil-to-Lymphocyte and Platelet-to-Lymphocyte Ratios in Predicting Intravenous Immunoglobulin Resistance with Kawasaki Disease
inferredcites →https://doi.org/10.1016/j.jpeds.2016.12.018openalex-snapshot
Efficacy of Four Scoring Systems in Predicting Intravenous Immunoglobulin Resistance in Children with Kawasaki Disease in a Children's Hospital in Beijing, North China
inferredcites →https://doi.org/10.1016/s0140-6736(11)61930-2openalex-snapshot
Efficacy of immunoglobulin plus prednisolone for prevention of coronary artery abnormalities in severe Kawasaki disease (RAISE study): a randomised, open-label, blinded-endpoints trial
inferredcites →https://doi.org/10.1016/s0140-6736(13)62298-9openalex-snapshot
Infliximab for intensification of primary therapy for Kawasaki disease: a phase 3 randomised, double-blind, placebo-controlled trial
inferredcites →https://doi.org/10.1093/oxfordjournals.eurheartj.a062105openalex-snapshot
On a possible role for calcium antagonists in atherosclerosis. A personal view
inferredcites →https://doi.org/10.1097/00006454-199812000-00009openalex-snapshot
Intravenous gamma-globulin treatment and retreatment in Kawasaki disease
inferredcites →https://doi.org/10.1097/inf.0b013e31815922b5openalex-snapshot
Analysis of Potential Risk Factors Associated With Nonresponse to Initial Intravenous Immunoglobulin Treatment Among Kawasaki Disease Patients in Japan
inferredcites →https://doi.org/10.1097/inf.0b013e3181f6fe2aopenalex-snapshot
Abnormal Liver Panel in Acute Kawasaki Disease
inferredcites →https://doi.org/10.1097/inf.0b013e31828e887fopenalex-snapshot
Novel Predictors of Intravenous Immunoglobulin Resistance in Chinese Children with Kawasaki Disease
inferredcites →https://doi.org/10.1109/tkde.2002.1000348openalex-snapshot
An instance-weighting method to induce cost-sensitive trees
inferredcites →https://doi.org/10.1111/apa.14418openalex-snapshot
Japanese scoring systems to predict resistance to intravenous immunoglobulin in Kawasaki disease were unreliable for Caucasian Israeli children
inferredcites →https://doi.org/10.1136/bmj.i6openalex-snapshot
Net benefit approaches to the evaluation of prediction models, molecular markers, and diagnostic tests
inferredcites →https://doi.org/10.1136/heartjnl-2012-302126openalex-snapshot
Intravenous immunoglobulin plus corticosteroid to prevent coronary artery abnormalities in Kawasaki disease: a meta-analysis
inferredcites →https://doi.org/10.1161/01.cir.0000145143.19711.78openalex-snapshot
Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease
inferredcites →https://doi.org/10.1161/atvbaha.110.208181openalex-snapshot
Risk Factor Differences for Aortic Versus Coronary Calcified Atherosclerosis
inferredcites →https://doi.org/10.1161/cir.0000000000000484openalex-snapshot
Diagnosis, Treatment, and Long-Term Management of Kawasaki Disease: A Scientific Statement for Health Professionals From the American Heart Association
inferredcites →https://doi.org/10.1161/circulationaha.105.592865openalex-snapshot
Prediction of Intravenous Immunoglobulin Unresponsiveness in Patients With Kawasaki Disease
inferredcites →https://doi.org/10.1186/s13052-018-0475-zopenalex-snapshot
A comparison of efficacy of six prediction models for intravenous immunoglobulin resistance in Kawasaki disease
inferredcites →https://doi.org/10.1198/000313008x370302openalex-snapshot
Decision Analysis for the Evaluation of Diagnostic Tests, Prediction Models, and Molecular Markers
inferredcites →https://doi.org/10.1542/peds.63.2.175openalex-snapshot
Kawasaki Disease: Effect of Treatment on Coronary Artery Involvement
inferredcites →https://doi.org/10.3389/fnbot.2013.00021openalex-snapshot
Gradient boosting machines, a tutorial
inferredcites →https://doi.org/10.48550/arxiv.1201.0490openalex-snapshot
Scikit-learn: Machine Learning in Python

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.2139/ssrn.4533208openalex-extracted
inferred← citeshttps://doi.org/10.1007/978-3-030-58080-3_83-1openalex-snapshot
Artificial Intelligence in Clinical Immunology
inferred← citeshttps://doi.org/10.1007/978-3-030-64573-1_83openalex-snapshot
Artificial Intelligence in Clinical Immunology
inferred← citeshttps://doi.org/10.1007/s00246-022-02973-2openalex-snapshot
Association of Genetic Polymorphisms in Kawasaki Disease with the Response to Intravenous Immunoglobulin Therapy
inferred← citeshttps://doi.org/10.1007/s10067-023-06502-1openalex-snapshot
A simple scoring model based on machine learning predicts intravenous immunoglobulin resistance in Kawasaki disease
inferred← citeshttps://doi.org/10.1007/s40272-025-00693-7openalex-snapshot
Learning-Based Models for Predicting IVIG Resistance and Coronary Artery Lesions in Kawasaki Disease: A Review of Technical Aspects and Study Features
inferred← citeshttps://doi.org/10.1016/b978-0-443-15688-5.00038-3openalex-snapshot
Artificial intelligence in pediatric congenital and acquired heart disease
inferred← citeshttps://doi.org/10.1016/j.envsoft.2023.105812openalex-snapshot
CIMCA: Infusing computational intelligence in multi-criteria analysis to assess groundwater potential for recharge
inferred← citeshttps://doi.org/10.1016/j.hjc.2024.08.003openalex-snapshot
Intelligent diagnosis of Kawasaki disease from real-world data using interpretable machine learning models
inferred← citeshttps://doi.org/10.1016/j.isci.2025.112004openalex-snapshot
A machine learning-based model to predict intravenous immunoglobulin resistance in Kawasaki disease
inferred← citeshttps://doi.org/10.1016/j.jbi.2020.103653openalex-snapshot
A prediction and interpretation framework of acute kidney injury in critical care
inferred← citeshttps://doi.org/10.1016/j.meadig.2026.100056openalex-snapshot
An explainable ensemble machine learning framework for predicting IVIG resistance in Kawasaki disease
inferred← citeshttps://doi.org/10.1016/j.semarthrit.2023.152213openalex-snapshot
Understanding the role and adoption of artificial intelligence techniques in rheumatology research: An in-depth review of the literature
inferred← citeshttps://doi.org/10.1038/s41390-023-02519-zopenalex-snapshot
Intravenous immunoglobulin resistance in Kawasaki disease patients: prediction using clinical data
inferred← citeshttps://doi.org/10.1038/s41390-023-02558-6openalex-snapshot
Risk-prediction models for intravenous immunoglobulin resistance in Kawasaki disease: Risk-of-Bias Assessment using PROBAST
inferred← citeshttps://doi.org/10.1038/s41598-021-99105-2openalex-snapshot
Predicting bloodstream infection outcome using machine learning
inferred← citeshttps://doi.org/10.1080/07853890.2022.2031273openalex-snapshot
Nomogram to predict risk of resistance to intravenous immunoglobulin in children hospitalized with Kawasaki disease in Eastern China
inferred← citeshttps://doi.org/10.1080/1744666x.2023.2238122openalex-snapshot
The state of play in tools for predicting immunoglobulin resistance in Kawasaki disease
inferred← citeshttps://doi.org/10.1097/inf.0000000000003919openalex-snapshot
Research on Early Identification Model of Intravenous Immunoglobulin Resistant Kawasaki Disease Based on Gradient Boosting Decision Tree
inferred← citeshttps://doi.org/10.1177/09733698241255915openalex-snapshot
Current Status of Machine Learning for Precision Rheumatology: Are We There Yet?
inferred← citeshttps://doi.org/10.1186/s12874-026-02893-2openalex-snapshot
Quality and performance of machine learning versus logistic regression for predicting IVIG resistance in Kawasaki disease: a PROBAST+AI systematic comparison
inferred← citeshttps://doi.org/10.1186/s12887-025-06082-wopenalex-snapshot
Explainable deep learning algorithm for distinguishing IVIG-Resistant Kawasaki disease in Shandong peninsula, China
inferred← citeshttps://doi.org/10.1186/s12911-026-03494-1openalex-snapshot
Machine learning prediction models for intravenous immunoglobulin resistance in Kawasaki disease: a meta-analysis
inferred← citeshttps://doi.org/10.1186/s12969-026-01269-6openalex-snapshot
Design of a prediction system for intravenous immunoglobulin resistance in hospitalized Kawasaki disease patients with artificial intelligence based on machine learning
inferred← citeshttps://doi.org/10.1186/s13052-025-01889-wopenalex-snapshot
Establishment and validation of risk prediction model to predict intravenous immunoglobulin-resistance in Kawasaki disease based on meta-analysis of 15 cohorts
inferred← citeshttps://doi.org/10.1186/s13052-025-01964-2openalex-snapshot
A visualized nomogram to predict intravenous immunoglobulin resistance in Kawasaki disease: a study based on the population in Southern China
inferred← citeshttps://doi.org/10.1186/s13052-025-02158-6openalex-snapshot
Value of the neutrophil percentage-to-albumin ratio in predicting intravenous Immunoglobulin resistance in Kawasaki disease: a retrospective cohort study
inferred← citeshttps://doi.org/10.12998/wjcc.v12.i23.5304openalex-snapshot
Application of artificial intelligence in the diagnosis and treatment of Kawasaki disease
inferred← citeshttps://doi.org/10.1371/journal.pone.0253675openalex-snapshot
Correction: A machine learning approach to predict intravenous immunoglobulin resistance in Kawasaki disease patients: A study based on a Southeast China population
inferred← citeshttps://doi.org/10.1371/journal.pone.0314995openalex-snapshot
Enhancing generalization in a Kawasaki Disease prediction model using data augmentation: Cross-validation of patients from two major hospitals in Taiwan
inferred← citeshttps://doi.org/10.1371/journal.pone.0327564openalex-snapshot
Clinical prediction of intravenous immunoglobulin-resistant Kawasaki disease based on interpretable Transformer model
inferred← citeshttps://doi.org/10.1542/peds.2022-059175openalex-snapshot
Prediction Models for Intravenous Immunoglobulin Resistance in Kawasaki Disease: A Meta-analysis
inferred← citeshttps://doi.org/10.20868/upm.thesis.72300openalex-snapshot
Data-driven approaches in rheumatology: learning from real-world data
inferred← citeshttps://doi.org/10.21203/rs.3.rs-1215051/v1openalex-snapshot
A Simple Scoring Model Based on Machine Learning Predicts Intravenous Immunoglobulin Resistance in Kawasaki Disease
inferred← citeshttps://doi.org/10.21203/rs.3.rs-1215051/v2openalex-snapshot
A Simple Scoring Model Based on Machine Learning Predicts Intravenous Immunoglobulin Resistance in Kawasaki Disease
inferred← citeshttps://doi.org/10.3389/fcvm.2023.1164530openalex-snapshot
Evaluation of Formosa score and diagnostic sensitivity and specificity of four Asian risk scores for predicting intravenous immunoglobulin resistance in Kawasaki disease: a bivariate meta-analysis
inferred← citeshttps://doi.org/10.3389/fimmu.2022.901872openalex-snapshot
Systems biology and artificial intelligence analysis highlights the pleiotropic effect of IVIg therapy in autoimmune diseases with a predominant role on B cells and complement system
inferred← citeshttps://doi.org/10.3390/jcm11237072openalex-snapshot
Artificial Intelligence in Pediatric Cardiology: A Scoping Review
inferred← citeshttps://doi.org/10.3991/ijoe.v22i02.58737openalex-snapshot
Federated Learning with Adaptive Intermediate Model Selection for Predicting IVIG Resistance in Kawasaki Disease
inferred← citeshttps://doi.org/10.51131/ijpccr/v4i2.23.11openalex-snapshot
Heart Disease Prediction using Artificial Intelligence and Machine Learning
inferred← citeshttps://doi.org/10.5863/1551-6776-27.7.669openalex-snapshot
Predicting Intravenous Immunoglobulin Resistance Among North American Children Hospitalized With Kawasaki Disease
inferred← citeshttps://doi.org/10.59492/kd.2023.1.1.e7openalex-snapshot
Epidemiology and Clinical Outcomes of Refractory Kawasaki Disease in South Korea
inferred← citeshttps://doi.org/10.59492/kd.2024.2.2.e6openalex-snapshot
Recent Machine Learning Applications in Kawasaki Disease Research
inferred← citeshttps://doi.org/10.9794/jspccs.41.113openalex-snapshot
Research on Kawasaki Disease in the Data-Driven Era: New Epidemiology, Omics Data, and Artificial Intelligence
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.