ArticlePediatric research2024
Reassessing acquired neonatal intestinal diseases using unsupervised machine learning.
Article in Pediatric research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed, 14 citations in OpenAlex.
- Distinct clinical patterns of preterm infants vulnerable to intestinal injury identified by unsupervised clustering.Pediatric research · 2026Article
- Does the initial surgical approach for SIP matter? EBM lesson: Kaplan-Meier Curve.Journal of perinatology : official journal of the California Perinatal Association · 2026Article
- "Necrotizing enterocolitis": a paradigm shift.Pediatric research · 2026Article
- Emerging role of artificial intelligence in necrotizing enterocolitis and implementation challenges.Pediatric research · 2026Article
- Clinical Impact of the PDA and Its Management on Outcomes of Preterm Infants with NEC: A Review.American journal of perinatology · 2026Review
- Neonatal microbiome in the multiomics era: development and its impact on long-term health.Pediatric research · 2025Review
- AI models in clinical neonatology: a review of modeling approaches and a consensus proposal for standardized reporting of model performance.Pediatric research · 2025Review
- Changes in the Incidence and Severity of NEC over the Last Decade: A Single-Center Study.Journal of clinical medicine · 2025Article
- The conundrum of intestinal injury in preterm infants receiving mother's own milk.Journal of perinatology : official journal of the California Perinatal Association · 2025Review
- Struggling to Understand the NEC Spectrum-Could the Integration of Metabolomics, Clinical-Laboratory Data, and Other Emerging Technologies Help Diagnosis?Metabolites · 2024Review
- Surgery for intestinal injuries in very preterm infants: a Norwegian population-based study with a new approach to disease classification.BMJ paediatrics open · 2024Article
- Understanding necrotizing enterocolitis endotypes and acquired intestinal injury phenotypes from a historical and artificial intelligence perspective.Frontiers in pediatrics · 2024Review
- Article
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Authors and funding
10 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundAcquired neonatal intestinal diseases have an array of overlapping presentations and are often labeled under the dichotomous classification of necrotizing enterocolitis (which is poorly defined) or spontaneous intestinal perforation, hindering more precise diagnosis and research. The objective of this study was to take a fresh look at neonatal intestinal disease classification using unsupervised machine learning.
methodsPatients admitted to the University of Florida Shands Neonatal Intensive Care Unit January 2013-September 2019 diagnosed with an intestinal injury, or had imaging findings of portal venous gas, pneumatosis, abdominal free air, or had an abdominal drain placed or exploratory laparotomy during admission were included. Congenital gastroschisis, omphalocele, intestinal atresia, malrotation were excluded. Data was collected via retrospective chart review with subsequent hierarchal, unsupervised clustering analysis.
resultsFive clusters of intestinal injury were identified: Cluster 1 deemed the "Low Mortality" cluster, Cluster 2 deemed the "Mature with Inflammation" cluster, Cluster 3 deemed the "Immature with High Mortality" cluster, Cluster 4 deemed the "Late Injury at Full Feeds" cluster, and Cluster 5 deemed the "Late Injury with High Rate of Intestinal Necrosis" cluster.
conclusionUnsupervised machine learning can be used to cluster acquired neonatal intestinal injuries. Future study with larger multicenter datasets is needed to further refine and classify types of intestinal diseases. IMPACT: Unsupervised machine learning can be used to cluster types of acquired neonatal intestinal injury. Five major clusters of acquired neonatal intestinal injury are described, each with unique features. The clusters herein described deserve future, multicenter study to determine more specific early biomarkers and tailored therapeutic interventions to improve outcomes of often devastating neonatal acquired intestinal injuries.
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