Federal Grant Award Summary

The National Institute of Biomedical Imaging and Bioengineering (NIBIB) awarded a Project Grant of $174,861 to the University of California, Los Angeles, effective March 10, 2026, with completion scheduled for February 28, 2030, under the Discovery and Applied Research for Technological Innovations to Improve Human Health program (CFDA 93.286). This award supports the development and external validation of artificial intelligence and machine learning algorithms designed to predict pediatric postoperative complications using physiological waveform data and electronic health record information. The research addresses a critical clinical need, as postoperative complications occur in 9-14% of pediatric surgical cases annually in the United States, yet existing predictive models have limited predictive capability beyond mortality. The project will leverage hemodynamic data and waveform data from pulse oximetry plethysmography, arterial pressure waveforms, and electrocardiograms—data elements previously underutilized in pediatric perioperative outcome prediction.

The primary objective of this award is to support Dr. Wingert's career development as a leader in perioperative pediatrics research through structured mentorship and training in artificial intelligence and machine learning methodologies, waveform analysis, and clinical decision support implementation. Deliverables include high-performing, implementable prediction models for pediatric perioperative complications and the advancement of Dr. Wingert's expertise in applying advanced computational and statistical approaches to clinical research. The project aims to fill knowledge gaps in pediatric perioperative research and generate tools that can inform clinical decision-making and improve patient outcomes in pediatric surgical settings.