LLMs for Cardiovascular Risk Prediction
LLMs for Cardiovascular Risk Prediction
A video-augmented VR framework coupling a physical ROS 2 autonomous vehicle to an immersive passenger view that combines synchronized motion, live onboard video, and navigation decisions.
A dual-channel UDP architecture transmitting vehicle state and video independently to maintain real-time physical–virtual consistency.
An experimental characterization over 20 closed-loop trials quantifying synchronization accuracy, latency, frame delivery, and decision-display fidelity.
Publications:
J. Maliha and M. R. Kabir, “LLMs for Cardiovascular Risk Prediction from Structured Clinical Data,” 3rd International Conference on Intelligent Systems, Blockchain, and Communication Technologies (ISBCom), 2026.