Additional file 2 of Machine learning model for predicting severe infection in children with idiopathic nephrotic syndrome: multicenter retrospective study

Additional file 2 of Machine learning model for predicting severe infection in children with idiopathic nephrotic syndrome: multicenter retrospective study

Supplementary Material 2: Supplementary Table S1. General variables and definitions of severe infection. Supplementary Table S2. Baseline characteristics of patients in the training, test and validation cohorts. Supplementary Table S3. Hyper-parameter settings of the proposed model. Supplementary Ta...

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Détails bibliographiques
Auteur principal: Sijie Yu (8895605) (author)
Autres auteurs: Wenhao Tang (839411) (author), De Zhang (6832625) (author), Fuwei Shen (22685936) (author), Anshuo Wang (17150164) (author), Han Chen (228557) (author), Hongxing Chen (610873) (author), Fanghong Zhang (20356512) (author), Li Xiao (307908) (author), Yan Li (23143) (author), Zongwen Chen (13843126) (author), Li Wang (15202) (author), Mo Wang (152951) (author), Haiping Yang (559756) (author), Qiu Li (13990651) (author)
Publié: 2025
Sujets:
Microbiology
Genetics
Molecular Biology
Immunology
Infectious Diseases
Virology
Biological Sciences not elsewhere classified
Mathematical Sciences not elsewhere classified
Idiopathic nephrotic syndrome
Severe infection
Children
Machine learning
Prediction model
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Résumé:Supplementary Material 2: Supplementary Table S1. General variables and definitions of severe infection. Supplementary Table S2. Baseline characteristics of patients in the training, test and validation cohorts. Supplementary Table S3. Hyper-parameter settings of the proposed model. Supplementary Table S4. Univariate analysis of adverse outcomes in critically infected patients.

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