Neonatal Outcome

Neonatal outcome research focuses on improving the health and survival of newborns, primarily through early detection of risks and timely interventions. Current research employs machine learning, particularly deep learning models like convolutional neural networks (CNNs) and multi-task learning frameworks, to analyze diverse data sources including cardiotocography (CTG), brain imaging (MRI, ultrasound), and audio recordings (chest sounds, resuscitation videos) to predict adverse outcomes and optimize care. These advancements offer the potential to significantly improve neonatal care by enabling earlier diagnosis of conditions like respiratory distress and facilitating more effective resuscitation techniques, ultimately leading to better outcomes for infants.