Case Study: Children’s National Hospital improves pediatric COVID-19 diagnostics with Rhino Federated Computing

Children’s National Hospital and Rhino Health Pave the Way for Enhanced Pediatric Diagnostics with Federated Learning

Children's National Hospital faced the challenge of accurately diagnosing conditions like COVID-19 in pediatric patients using chest X-rays while ensuring strict data privacy. They partnered with Rhino Federated Computing and used the Rhino Health Federated Computing Platform to address this.

Rhino Federated Computing implemented a federated learning solution using Vision Transformers and Self-Supervised Learning. This allowed the hospital to collaboratively train an AI model across multiple sites without sharing sensitive patient data. The solution significantly improved the model's accuracy in distinguishing between COVID-19 and non-COVID-19 cases in pediatric chest X-rays, as evidenced by a higher Area Under the Precision-Recall Curve, paving the way for more secure and effective pediatric diagnostics.

Children's National Hospital