ArticleActa paediatrica (Oslo, Norway : 1992)2021
Bronchopulmonary dysplasia predicted at birth by artificial intelligence.
Article in Acta paediatrica (Oslo, Norway : 1992), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 3 of them syntheses that pooled it.
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Who cites it
21 citing papers in PubMed, 3 syntheses or guidelines pooled it, 38 citations in OpenAlex.
- Opportunities and Challenges of Using Artificial Intelligence in Predicting Clinical Outcomes and Length of Stay in Neonatal Intensive Care Units: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Clinical and Imaging Data-based Machine Learning for Early Diagnosis of Bronchopulmonary Dysplasia: A Meta-analysis.Current medical imaging · 2025Pooled it
- Prediction Models for Bronchopulmonary Dysplasia in Preterm Infants: A Systematic Review.Frontiers in pediatrics · 2022Pooled it
- Artificial intelligence and digital technologies transforming neonatal respiratory assessment: a scoping review.Journal of perinatology : official journal of the California Perinatal Association · 2026Review
- Video-based artificial intelligence for automated neonatal respiratory monitoring.European journal of pediatrics · 2026Article
- Transforming Pediatric Care Through AI: Bridging the Digital Divide in Health Informatics.Online journal of public health informatics · 2026Article
- Defining endotypes of bronchopulmonary dysplasia in preterm infants to improve precision-based therapies.JCI insight · 2025Review
- Steroid Use for Established Bronchopulmonary Dysplasia: A Systematic Review and Meta-Analysis.Children (Basel, Switzerland) · 2025Review
- Enhancing bronchopulmonary dysplasia prediction in preterm infants using artificial intelligence and multimodal data integration.Frontiers in pediatrics · 2025Review
- Combining artificial intelligence and conventional statistics to predict bronchopulmonary dysplasia in very preterm infants using routinely collected clinical variables.Pediatric pulmonology · 2024Article
- Artificial Intelligence in Pediatrics: Learning to Walk Together.Turkish archives of pediatrics · 2024Article
- Bridging the Gap: Exploring Bronchopulmonary Dysplasia through the Lens of Biomedical Informatics.Journal of clinical medicine · 2024Review
- Prevention of Inflammatory Disorders in the Preterm Neonate: An Update with a Special Focus on Bronchopulmonary Dysplasia.Neonatology · 2024Review
- Prediction of bronchopulmonary dysplasia in very preterm infants: competitive risk model nomogram.Frontiers in pediatrics · 2024Article
- The past, current, and future of neonatal intensive care units with artificial intelligence: a systematic review.NPJ digital medicine · 2023Review
- Risk factors and machine learning prediction models for bronchopulmonary dysplasia severity in the Chinese population.World journal of pediatrics : WJP · 2023Article
- Neonatal sequential organ failure assessment score within 72 h after delivery reliably predicts bronchopulmonary dysplasia in very preterm infants.Frontiers in pediatrics · 2023Article
- Artificial intelligence in bronchopulmonary dysplasia- current research and unexplored frontiers.Pediatric research · 2023Article
- Co-expression network analysis for identification of novel biomarkers of bronchopulmonary dysplasia model.Frontiers in pediatrics · 2022Article
- Bronchopulmonary dysplasia predicted at birth by artificial intelligence.Acta paediatrica (Oslo, Norway : 1992) · 2021Article
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Authors and funding
14 authors at 5 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
aimTo develop a fast bedside test for prediction and early targeted intervention of bronchopulmonary dysplasia (BPD) to improve the outcome.
methodsIn a multicentre study of preterm infants with gestational age 24-31 weeks, clinical data present at birth were combined with spectral data of gastric aspirate samples taken at birth and analysed using artificial intelligence. The study was designed to develop an algorithm to predict development of BPD. The BPD definition used was the consensus definition of the US National Institutes of Health: Requirement of supplemental oxygen for at least 28 days with subsequent assessment at 36 weeks postmenstrual age.
resultsTwenty-six (43%) of the 61 included infants developed BPD. Spectral data analysis of the gastric aspirates identified the most important wave numbers for classification and surfactant treatment, and birth weight and gestational age were the most important predictive clinical data. By combining these data, the resulting algorithm for early diagnosis of BPD had a sensitivity of 88% and a specificity of 91%.
conclusionA point-of-care test to predict subsequent development of BPD at birth has been developed using a new software algorithm allowing early targeted intervention of BPD which could improve the outcome.
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