NYC Gazette

Dr. Youshan Zhang, an assistant professor at the Katz School of Science and Health, has secured a $175,000 grant from the National Science Foundation (NSF) to enhance cardiomegaly diagnosis in animals through an AI-driven tool. Cardiomegaly, or heart enlargement, is a significant early sign of heart disease in dogs and humans. Traditionally diagnosed via manual analysis of chest X-rays using the Vertebral Heart Scale (VHS), this process can be slow and error-prone.

Dr. Zhang’s project, "Cardiac Disease Detection with AI for Veterinary Medicine," seeks to automate the VHS process with improved accuracy and speed using deep learning models. “The primary goal of the project is to bridge the gap between traditional clinical methods and advanced AI models,” said Dr. Zhang.

To build trust in AI-generated results among clinicians, especially those without deep learning expertise, the project will integrate VHS metrics into its framework. This integration aims to enhance model transparency and accuracy while making diagnosis more intuitive for veterinary professionals.

The research builds on Dr. Zhang’s previous work published in Scientific Reports involving the Regressive Vision Transformer (RVT) for assessing cardiomegaly in dogs. The new project outlines three goals: developing new detection models using a perpendicular fully connected layer (PFCL), creating automatic report generation tools with minimal data training, and designing a user-friendly software interface for clinicians.

“By developing a more precise and accessible diagnostic tool, the project aims to lower the cost of cardiomegaly detection while improving diagnostic accuracy and reducing stress for pet owners,” said Dr. Zhang.