Explore a comprehensive presentation on artificial intelligence in pediatric cardiac imaging delivered by Dr. Shelby Kutty, Helen Taussig Professor and Director of Pediatric & Congenital Cardiology at Johns Hopkins School of Medicine, during the American Society of Echocardiography's 34th Annual Scientific Sessions. Delve into the current state of non-artificial intelligence in pediatric cardiac imaging and its potential challenges. Gain insights into essential AI terminology, including machine learning concepts and neural network components. Discover practical applications of AI in healthcare, such as ECG analysis for Long QT Syndrome diagnosis and fetal cardiac diagnosis. Examine the use of support vector machines for outcome prediction and understand the specific challenges AI presents in healthcare. Reflect on the rapid advancements in AI technology and its impact on pediatric cardiac imaging.
Overview
Syllabus
Intro
Non-artificial intelligence & pediatric cardiac imaging Do we have a problem with that?
Artificial Intelligence Terminology
Machine learning: supervised & unsupervised
Components of Neural Networks
Types of Neural Networks
ECG to Diagnose Long QT Syndrome
Fetal Cardiac Diagnosis
Support Vector Machine: Outcome Prediction
Al in health care presents specific challenges
We've come a long way fast
Taught by
Johns Hopkins Medicine
