Bronchopulmonary dysplasia is a chronic lung disease of prematurity marked by impaired alveolar development and prolonged oxygen dependence. More…
It can hinder growth and neurodevelopment and can be fatal, making accurate early risk stratification a priority in neonatal intensive care. Clinicians often lack reliable tools to identify which infants will deteriorate. A new study shows a time‑series machine learning approach that forecasts risk more precisely and could enable earlier, individualized interventions.
Researchers at UC Davis Health (Sacramento, CA, USA), in collaboration with the University of Rochester Medicine (Rochester, NY, USA), developed a dynamic risk prediction model for bronchopulmonary dysplasia (BPD), a serious lung condition affecting extremely preterm infants. Published in The Journal of Pediatrics under the title “Time-Series Machine Learning for Prediction of Bronchopulmonary Dysplasia,” the study introduces a machine-learning approach that continuously updates risk estimates over time, addressing limitations of existing assessment tools in this highly vulnerable population…