Case Study: Leading National Premier Children Hospital achieves earlier PVL detection with Excellarate predictive analytics

Children’s Hospital Using Predictive Analytics to Identify Accurate Diagnoses Earlier and Implement More Effective, Targeted Intervention

Leading National Premier Children Hospital worked with Excellarate to address the challenge of detecting periventricular leukomalacia (PVL) earlier in premature infants, since the condition can be difficult to diagnose and may not appear until months after initial symptoms. The hospital sought a predictive analytics approach to identify high-risk newborns sooner and support more targeted clinical intervention.

Excellarate implemented a patient-specific predictive analytics accelerator for clinical decision support, combining machine learning, nonlinear dynamics, wavelet transform analysis, and clinical expertise to analyze vital signs, blood gas, and lab results after neonatal heart surgery. The solution was able to identify critical risk patterns within the first 12 hours after surgery and delivered 92% accuracy, helping physicians intervene earlier and reduce PVL-related complications, readmissions, and expensive downstream care.