AI-Powered Synapsis AI Enhances Patient Care Through Advanced Record Analysis

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Dyania Health’s Synapsis AI uses NVIDIA technology to analyze decades of patient records, aiding clinicians in delivering faster, personalized care.

Artificial intelligence is transforming healthcare by enabling care teams to focus more on patients and less on administrative tasks. One notable example is Dyania Health’s Synapsis AI, a clinical reasoning engine designed to analyze decades of patient records and provide actionable insights for clinicians. This innovative tool is powered by NVIDIA technologies, ensuring secure and efficient processing of sensitive medical data.

How Synapsis AI Works

Hospitals often store decades of patient data in free-text formats, including physicians’ notes, operative reports, imaging results, and discharge summaries. Analyzing this data manually is time-consuming and labor-intensive. Synapsis AI addresses this challenge by scanning and connecting findings across all patient records, even those years apart. Its output includes clinical signals traceable to their source, helping care teams identify which patients require attention and why. Importantly, clinicians remain central to the decision-making process, reviewing the AI-generated evidence before taking action.

Data Security and Onsite Processing

Synapsis AI operates within a health system’s firewall, ensuring that patient data never leaves the hospital premises. This approach not only safeguards sensitive information but also streamlines workflows by automating chart reviews. The AI platform is built and optimized using NVIDIA NeMo open libraries and TensorRT technologies, enabling faster and more efficient performance on GPU servers located within the hospital.

Real-World Applications

The Cleveland Clinic leveraged Synapsis AI to analyze records from over 7,800 aortic valve replacement patients treated between 2005 and 2021. By reviewing echocardiograms and other data, the AI developed predictive models for valve deterioration and reintervention risks at three-, five-, and ten-year intervals. This analysis, which would have taken clinicians years to complete manually, was performed in a fraction of the time. Dr. Lars Svensson, chief of the Heart, Vascular & Thoracic Institute at Cleveland Clinic, highlighted the potential of this technology to enhance patient outcomes and enable more personalized care.

The platform’s capabilities extend beyond cardiology. It can assist in identifying patients eligible for clinical trials, closing care gaps in oncology, and populating clinical registries, demonstrating its versatility across various healthcare challenges.