Using AI to Combat New York's Leading Cause of Death

Empire AI for Medical Imaging and Diagnosis
Prof. Pingkun Yan | RPI

Challenge
Cardiovascular disease is the leading cause of death in New York State, responsible for 54,000 deaths annually. Early detection is critical, yet diagnosis often depends on interpreting complex imaging data that can vary in quality and require significant time and expertise.

As imaging technologies produce increasingly large datasets, clinicians face growing challenges in analyzing this information consistently. Human interpretation can vary, and subtle indicators of disease may be overlooked.

Researcher’s Approach Using Empire AI
The team develops AI models that analyze imaging and patient data together.
Empire AI enables training on large imaging datasets and clinical records.

Empire AI Enables

• Faster, more accurate diagnostics
• Integration of diverse data
• Scalable AI development

Without Empire AI, Models would be smaller and less accurate.

Potential Impacts

• Improves early detection of cardiovascular disease
• Reduces mortality through faster and more accurate diagnosis
• Lowers healthcare costs by streamlining clinical workflows
• Enhances consistency and quality of care across providers

Read more about Prof. Yan and his research:

• Prof. Yan’s bio at RPI
• Rensselaer Team Aims To Pave Way for Robust AI in Medical Imaging
• Medical multimodal multitask foundation model for lung cancer screening 
• Deep learning predicts cardiovascular disease risks from lung cancer screening low dose computed tomography