AIMC Topic: Bronchopulmonary Dysplasia
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Development and external validation of a machine learning model to predict bronchopulmonary dysplasia using dynamic factors.
Scientific reports
Apr 19, 2025
We hypothesized that incorporating postnatal dynamic factors would enhance the prediction accuracy of bronchopulmonary dysplasia in preterm infants. This retrospective cohort study included neonates born before 32 weeks of gestation at Seoul National...
Machine Learning Identification of Neutrophil Extracellular Trap-Related Genes as Potential Biomarkers and Therapeutic Targets for Bronchopulmonary Dysplasia.
International journal of molecular sciences
Mar 31, 2025
Neutrophil extracellular traps (NETs) play a key role in the development of bronchopulmonary dysplasia (BPD), yet their molecular mechanisms in contributing to BPD remain unexplored. Using the GSE32472 dataset, which includes 100 blood samples from p...
Automated Euler number of the alveolar capillary network based on deep learning segmentation with verification by stereological methods.
Journal of microscopy
Jan 31, 2025
Diseases like bronchopulmonary dysplasia (BPD) affect the development of the pulmonary vasculature, including the alveolar capillary network (ACN). Since pulmonary development is highly dependent on angiogenesis and microvascular maturation, ACN inve...
Early prediction of mortality and morbidities in VLBW preterm neonates using machine learning.
Pediatric research
Oct 8, 2024
BACKGROUND: Predicting mortality and specific morbidities before they occur may allow for interventions that may improve health trajectories.
Combining artificial intelligence and conventional statistics to predict bronchopulmonary dysplasia in very preterm infants using routinely collected clinical variables.
Pediatric pulmonology
Aug 16, 2024
BACKGROUND: Prematurity is the strongest predictor of bronchopulmonary dysplasia (BPD). Most previous studies investigated additional risk factors by conventional statistics, while the few studies applying artificial intelligence, and specifically ma...
Using machine-learning models to predict extubation failure in neonates with bronchopulmonary dysplasia.
BMC pulmonary medicine
Jul 1, 2024
AIM: To develop a decision-support tool for predicting extubation failure (EF) in neonates with bronchopulmonary dysplasia (BPD) using a set of machine-learning algorithms.
A comprehensive study on machine learning models combining with oversampling for bronchopulmonary dysplasia-associated pulmonary hypertension in very preterm infants.
Respiratory research
May 8, 2024
BACKGROUND: Bronchopulmonary dysplasia-associated pulmonary hypertension (BPD-PH) remains a devastating clinical complication seriously affecting the therapeutic outcome of preterm infants. Hence, early prevention and timely diagnosis prior to pathol...
Deep Learning Model for Prediction of Bronchopulmonary Dysplasia in Preterm Infants Using Chest Radiographs.
Journal of imaging informatics in medicine
Mar 18, 2024
Bronchopulmonary dysplasia (BPD) is common in preterm infants and may result in pulmonary vascular disease, compromising lung function. This study aimed to employ artificial intelligence (AI) techniques to help physicians accurately diagnose BPD in p...
Early severity prediction of BPD for premature infants from chest X-ray images using deep learning: A study at the 28th day of oxygen inhalation.
Computer methods and programs in biomedicine
May 10, 2022
BACKGROUND AND OBJECTIVE: Bronchopulmonary dysplasia is a common respiratory disease in premature infants. The severity is diagnosed at the 56th day after birth or discharge by analyzing the clinical indicators, which may cause the delay of the best ...
An alternative method to measure the diffusing capacity of the lung for carbon monoxide in infants.
Pediatric pulmonology
Dec 19, 2017
BACKGROUND: Lung diffusion assessed by the uptake of carbon monoxide (DL ) and alveolar volume (V ) by inert gas dilution are readily assessed in cooperative older subjects; however, obtaining these measurements in infants has been much more difficul...
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