Detecting Abnormalities of Fetal Cardiac Using Deep Learning in Parallel Computing Environment

Deep learning has become a recent explosion in our everyday lives. Being one of the leading machine tools among various tools, deep contributes lot to image analysis and vision computer. This tool is considered enormous for analysis, especially detecting fetal cardiac abnormalities parallel computing environment. Screening congenital disease (CCD) challenging achieving accuracy terms diagnoses concerning manual process. Hence this proposed work, optimized ultrasound (USI) based Artificial Neural Network (ANN), tool, proven exploiting dissimilitude prognoses cardiomyopathies predicting perinatal mortality (CCD). Fetal Cardiac parameters are evaluated using myocardial performance index (MPI), biomarker global function providing statistics on periods during diastolic systolic phases. paper also discusses some potential trends application function.