Pauletta Irwin, Deborah Magee, Shannon Weiley, Sarah Teakel, Kelly Linden
Improving student success and retention in first-year nursing through embedded tutor support
Nurse education today
challenge accurately identifying classifying left ventricular hypertrophy lvh distinguishing hypertrophic cardiomyopathy hcm fabry disease reliance imaging techniques often requires expertise multiple specialists including cardiologists radiologists geneticists variability interpretation classification lvh leads inconsistent diagnoses lvh hcm fabry cardiomyopathy differentiated using t1 mapping cardiac magnetic resonance imaging mri however differentiation hcm fabry cardiomyopathy using echocardiography mri cine images challenging cardiologists proposed system named mri shortaxis view left ventricular hypertrophy classifier mslvhc highaccuracy standardized imaging classification model developed using ai trained mri shortaxis sax view cine images distinguish hcm fabry disease model achieved impressive performance f1score 0846 accuracy 0909 auc 0914 tested taipei veterans general hospital tvgh dataset additionally singleblinding study external testing using data taichung veterans general hospital tcvgh demonstrated reliability effectiveness model achieving f1score 0727 accuracy 0806 auc 0918 demonstrating models reliability usefulness ai model holds promise valuable tool assisting specialists diagnosing lvh diseases