MIT Partnership

Developing transformer-based architectures that can replicate clinical reasoning patterns, enabling AI systems to explain their diagnostic logic in human-understandable terms.

Creating unified models that can simultaneously process text, images, genomic data, and vital signs to provide comprehensive patient assessments with unprecedented accuracy.

Advancing differential privacy and homomorphic encryption techniques to enable collaborative medical AI training while maintaining strict patient privacy standards.

Building ultra-low latency AI systems that can provide instant clinical insights during patient encounters, emergency situations, and surgical procedures.