Automating Bone Age Assessment from Pediatric Xrays

Explore the automation of bone age assessment from pediatric X-rays in this informative lecture by Pranay Goel. Delve into the application of machine learning techniques for analyzing medical imaging data, specifically focusing on the assessment of skeletal maturity in children. Learn about the challenges and opportunities in developing automated systems for bone age estimation, which is crucial for evaluating growth disorders and predicting adult height. Gain insights into the intersection of artificial intelligence and pediatric radiology, and understand how these advancements can improve diagnostic accuracy and efficiency in clinical practice. This talk is part of the "Machine Learning for Health and Disease" program, which aims to bridge the gap between computational modeling and clinical problems in healthcare.