ArticleBosnian journal of basic medical sciences2022
An improved joint non-negative matrix factorization for identifying surgical treatment timing of neonatal necrotizing enterocolitis.
Article in Bosnian journal of basic medical sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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13 citing papers in PubMed, 1 synthesis or guideline pooled it, 13 citations in OpenAlex.
- Methods of identifying surgical Necrotizing Enterocolitis-a systematic review and meta-analysis.Pediatric research · 2025Pooled it
- Dual swin transformer for assisting in the diagnosis and surgical prediction of necrotizing enterocolitis.Pediatric research · 2026Article
- [Research progress in artificial intelligence for the diagnosis and management of diseases in preterm infants].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2026Review
- Machine Learning-Based Prediction of Surgical Intervention in Preterm Infants with Necrotizing Enterocolitis: A Retrospective Cohort Study.Children (Basel, Switzerland) · 2025Article
- New biomarkers to predict the need for surgery of necrotizing enterocolitis: a study based on abdominal X-ray radiomics and machine learning.Biomedical engineering online · 2025Article
- [Recent advances in artificial intelligence for auxiliary diagnosis and management of neonatal necrotizing enterocolitis].Zhongguo dang dai er ke za zhi = Chinese journal of contemporary pediatrics · 2025Review
- Use of CatBoost algorithm to identify the need for surgery in infants with necrotizing enterocolitis.Frontiers in pediatrics · 2025Article
- Application of Pan-Omics Technologies in Research on Important Economic Traits for Ruminants.International journal of molecular sciences · 2024Review
- Machine learning-based analysis for prediction of surgical necrotizing enterocolitis in very low birth weight infants using perinatal factors: a nationwide cohort study.European journal of pediatrics · 2024Article
- Focused review on artificial intelligence for disease detection in infants.Frontiers in digital health · 2024Review
- Construction and evaluation of a risk model for adverse outcomes of necrotizing enterocolitis based on LASSO-Cox regression.Frontiers in pediatrics · 2024Article
- Understanding necrotizing enterocolitis endotypes and acquired intestinal injury phenotypes from a historical and artificial intelligence perspective.Frontiers in pediatrics · 2024Review
- State of the art review on machine learning and artificial intelligence in the study of neonatal necrotizing enterocolitis.Frontiers in pediatrics · 2023Review
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Authors and funding
12 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Neonatal necrotizing enterocolitis is a severe neonatal intestinal disease. Timely identification of surgical indications is essential for newborns in order to seek the best time for treatment and improve prognosis. This paper attempts to establish an algorithm model based on multimodal clinical data to determine the features of surgical indications and construct an auxiliary diagnosis model. The proposed algorithm adds hypergraph constraints on the two modal data based on Joint Nonnegative Matrix Factorization (JNMF), aiming to mine the higher-order correlations of the two data features. In addition, the adjacency matrix of the two kinds of data is used as a network regularization constraint to prevent overfitting. Orthogonal and L1-norm regulations were introduced to avoid feature redundancy and perform feature selection, respectively, and confirmed 14 clinical features. Finally, we used three classifiers, random forest, support vector machine, and logistic regression, to perform binary classification of patients requiring surgery. The results show that when the features selected by the proposed algorithm model are classified by random forest, the area under the ROC curve is 0.8, which has high prediction accuracy.
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