Big Data & AI for Pediatric Health
Harnessing advanced analytics, intelligent systems, and large-scale clinical data to uncover insights, support decision-making, and improve outcomes across pediatric care.
Georgia Tech researchers are using big data, artificial intelligence, and advanced sensing technologies to better understand pediatric health challenges and identify opportunities for earlier intervention, smarter clinical decisions, and more personalized care.
Explore our active and recent projects supporting pediatric innovation. Click a project below to view details.
Featured Projects
Modeling the Effects of Orthognathic Surgery on Obstructive Sleep Apnea
An AI-driven research project that uses medical imaging and clinical data to predict obstructive sleep apnea risk and evaluate how jaw surgery can improve airway function in pediatric patients.
FUSION: Surgical Risk Prediction
An AI-powered surgical planning project that analyzes clinical and procedural data to predict neurological risks during pediatric spinal fusion and support safer, more informed decision-making.
Clinic-to-Home Telemetry Trial
A feasibility study for continuous monitoring outside the clinic.
Remote Patient Data Platform
Secure pipeline for collecting and reviewing at-home measurements.
VR Therapy Engagement Study
Measuring adherence and engagement with guided VR therapy sessions.
Outcomes Dashboard & Reporting
A shared view of metrics to support program evaluation and reporting.