Federated learning for prenatal detection of interrupted aortic arch using fetal ultrasound imaging

Key Points

• Enhanced prenatal detection of interrupted aortic arch using federated learning methods.
• Detection accuracy improved significantly, achieving up to 85% accuracy based on ultrasound imaging analysis.
• Implementation utilized federated learning across multiple clinical sites without sharing sensitive data.
• Supports collaborative approaches to enhance machine learning applications in prenatal diagnostics.