Dyania Health and NVIDIA Partner to Advance Patient Care with Clinical Reasoning AI

JERSEY CITY, N.J., Nov. 13, 2026 /CourierPR/ -- Dyania Health has partnered with NVIDIA to bring its Synapsis AI clinical reasoning tool inside hospital firewalls, allowing health systems to analyze their entire patient populations' medical records for better patient care. This collaboration aims to leverage the power of AI to extract and interpret clinical information from vast medical records, enabling health systems to make more informed treatment decisions and improve patient outcomes.

Dyania Health’s Synapsis AI is designed to read and analyze a patient’s complete medical history, including notes, operative reports, imaging reports, and lab results. By using NVIDIA’s accelerated computing platform, the AI can process this information securely within the hospital’s own infrastructure, ensuring patient privacy and compliance with data protection regulations.

The partnership between Dyania Health and NVIDIA marks a significant step in the application of AI in healthcare.

One of the first applications of this technology is a study conducted with Cleveland Clinic, which analyzed the medical records of 7,812 patients who received an aortic valve replacement between 2005 and 2021. The study aimed to predict how long the replacement valve would last and whether a second procedure would be needed. Researchers reviewed up to 16 years of patient care, including narrative notes and echocardiogram reports, which are often challenging to capture in traditional registries.

Using Synapsis AI, the researchers identified the patient population and answered 88 clinical questions for each patient, covering the valve and its characteristics, co-existing conditions, laboratory trends, medications, follow-up ultrasound measurements, and later clinical events. The study produced a detailed clinical dataset in far less time than a manual review would take. Additionally, a predictive machine-learning model was trained to estimate the risk of valve failure and the timing of potential reinterventions for every patient.

The model found that the type of valve implanted was the strongest determinant of how quickly it deteriorated, while age and other medical conditions shaped whether and when a second procedure was performed. The analysis also highlighted the importance of follow-up information, such as heart ultrasounds following surgery, in improving predictive accuracy around future interventions. The tool is used to inform care decisions but requires external validation from clinicians.

Dyania Health’s Synapsis AI is built on NVIDIA’s AI Enterprise software stack, using the NVIDIA NeMo framework for model training and reinforcement learning. Inside the health system, Synapsis AI runs on NVIDIA TensorRT and TensorRT-LLM on the hospital’s own NVIDIA accelerated computing infrastructure, ensuring that inference stays within the hospital’s private network.

The companies are evaluating several NVIDIA technologies, including Confidential Computing for training and inference, Dynamo for distributed inference serving, Multi-Instance GPU for partitioning GPUs across concurrent clinical workloads, and scaling to many NVIDIA Blackwell Ultra GPUs as deployments move from batch processing toward near-real-time clinical insight at the point of care.

The collaboration aims to bring Synapsis AI on NVIDIA infrastructure to health systems in the U.S. and internationally, publish joint case studies, and integrate Synapsis AI with NVIDIA’s healthcare software stack. The ultimate goal is to continuously train predictive models that will help care teams make more accurate and timely decisions for their patients.