Publications by authors named "B W Eidem"
Article Synopsis
- Researchers aimed to create AI algorithms using 12-lead ECGs to detect left and right ventricular systolic dysfunction (LVSD and RVSD) in children, as early diagnosis can significantly reduce health risks.
- They analyzed data from over 10,000 pediatric patients and developed models that showed high accuracy in identifying LVSD and RVSD, outperforming existing models designed for adults.
- The findings suggest that specialized AI tools for children are more effective than those trained on adult data, highlighting the potential for better diagnostic procedures in pediatric cardiac health.
Article Synopsis
- AI-enabled ECGs can predict the sex of pediatric patients and analyze the effects of puberty on this prediction.
- The study utilized a convolutional neural network trained on ECG data from over 90,000 pediatric patients, dividing them into different age groups.
- The model showed 81% overall accuracy, especially discriminating well in postpubertal patients, indicating potential for effective use in pediatric cardiology.
International Congenital Heart Defects Awareness - Be an ASE Advocate!
J Am Soc Echocardiogr
March 2024