Using electronic health records to detect Noonan syndrome in pediatric patients

An early and accurate diagnosis is important for patients of genetic diseases. But many patients have to endure long diagnostic odysseys due to lack of recognition. Using Noonan syndrome as an example, this study sought to evaluate the utility of deep learning methods with electronic health record to detect these patients.

Speaker: Jing Chen, PhD, AssCistant Professor of Bioinformtics, University of Cincinnati

Obtain Zoom link by emailing epibiostat@ucsf.edu.