Zhengfeng Lai, Pranjali Vadlaputi, Daniel J Tancredi, Meena Garg, Robert I Koppel, Mera Goodman, Whitnee Hogan, Nicole Cresalia, Stephan Juergensen, Erlinda Manalo, Satyan Lakshminrusimha, Chen-Nee Chuah, Heather Siefkes
Critical Congenital Heart Disease (CCHD) screening that only uses oxygen saturation (SpO2), measured by pulse oximetry, fails to detect an estimated 900 US newborns annually. The addition of other pulse oximetry features such as perfusion index (PIx), heart rate, pulse delay and photoplethysmography characteristics may improve detection of CCHD, especially those with systemic blood flow obstruction such as Coarctation of the Aorta (CoA). To comprehensively study the most relevant features associated with CCHD, we investigated interpretable machine learning (ML) algorithms by using Recursive Feature Elimination (RFE) to identify an optimal subset of features...
November 2021: Annual International Conference of the IEEE Engineering in Medicine and Biology Society