RIT computing professor Linwei Wang, whose research is advancing non-invasive personalized healthcare for heart diseases, is receiving the Presidential Early Career Award for Scientists and Engineers (PECASE).
She and her group are also highly interested in applications in medical and healthcare challenges, especially for improving patient care in cardiac arrhythmia and other heart diseases.
This award supports the development of computational foundation for integrating physics-based models into data-driven inference, which later found application in a computational system for non-invasive imaging of patient-specific cardiac rhythm disorders.
Today, in a $3 million project funded by the National Institutes of Health, Wang is leading an international and multidisciplinary team of investigators to pursue the clinical use of this technology for guiding the interventional procedure for lethal ventricular arrhythmia.
Collaborating with experts in patient-specific cardiac modeling and high-performance computing, Wang and her team have been developing novel uncertainty quantification techniques that -- leveraging advances in active machine learning -- enables the propagation of uncertainty from the data used to model elements and develop future predictions.
Wang said this will help address the variability in personalized virtual organ models and help remove the major roadblock to the widespread adoption of these models in decision support.