Cardiac Mapping – Real Time Navigation & Guidance, ultralow latency AI/PhysArch

The aim of this presentation is to demonstrate the use of a advanced converge AI architecture which involves real-time utra low latency signal acquisition with inferencing that assists in navigation and guidance in Cardiac Mapping. Cardiac Mapping is diagnostic and therpeutic tool used for specific cardiac procedures utilized to treat Atrial Fibrillation, which occurs when a patient exhibits symptoms of an electrical rhythm disorder. This discussion will highlight the challenges associated with achieving low latency in image and signal inferences for anatomical and 3D object detection. Furthermore, by employing a RAG approach, along with suitable machine learning, deep learning models, and large language models, the AI-based architecture will illustrate how cardiac mapping can be performed more effectively and efficiently, thereby enhancing the patient's quality of life.
Agenda:

• Intro - Cardiac Mapping
• Converged AI Architecture using Signal Acquisition + Real Time Inferencing + Gen AI
• Concepts - Signal Acquisition + Image Acquisition + Time correlation
• Tokenization and key word assessment
• Demonstration of Cardiac Mapping
• Opportunities to expand the platform and architecture Challenges
• Q&A