{
  "id": 19808948,
  "title": "How AI Is Helping Care Teams Get Patients the Right Care, Sooner",
  "url": "https://urgent.news/2026/11/13/how-ai-is-helping-care-teams-get-patients-the-right-care-sooner",
  "topic": "ai",
  "section": "AI",
  "published": "2026-11-13T13:00:42.000Z",
  "source": {
    "name": "NVIDIA Blog",
    "slug": "nvidia-blog",
    "url": "https://blogs.nvidia.com/blog/how-ai-is-helping-care-teams/"
  },
  "original_language": "en",
  "account": "Artificial intelligence (AI) is revolutionizing healthcare by enabling care teams to deliver the right care to patients more swiftly. Hospitals and startups are deploying AI to tackle various aspects of healthcare, including connecting patients with clinical trials and aiding radiologists, hospital teams, and home-based patients. Clinicians retain their critical role, reviewing AI-generated insights and guiding decisions, with NVIDIA technologies serving as the backbone for these applications.\n\nOne such AI-driven initiative is Dyania Health, a New Jersey-based clinical AI firm that developed Synapsis AI. This robust clinical reasoning engine harnesses the wealth of patient history stored in hospitals' free-text records, which typically encompass notes, operative reports, imaging, pathology analyses, and discharge summaries. Synapsis AI integrates findings that could span years, providing clinicians with a comprehensive view of a patient's medical journey.\n\nSynapsis AI's output comprises clinical signals, each tied back to its source within the patient record, alerting care teams to potential issues and elucidating their reasons. It is essential to note that clinicians retain the final say in all decisions, as Synapsis AI operates as an assistive tool, revealing evidence from medical records that clinicians must still verify and act upon.\n\nSynapsis AI operates within the confines of a health system's firewall, utilizing NVIDIA-accelerated computing to process all patient records locally. This approach not only streamlines chart review for clinical teams but also ensures patient data remains within the hospital's jurisdiction. Dyania Health leverages NVIDIA's NeMo open libraries and TensorRT for model development and optimization, enabling Synapsis AI to process records rapidly and efficiently on the hospital's GPU servers.\n\nA testament to Synapsis AI's efficacy can be seen in its implementation at the Cleveland Clinic. In a study involving over 7,800 aortic valve replacement patients from 2005 to 2021, Synapsis AI analyzed each patient's record, encompassing post-surgical echocardiograms, to construct a predictive model forecasting valve deterioration and reintervention risk at the three-, five-, and ten-year points post-procedure. The AI platform successfully completed chart reviews across the entire cohort that would have necessitated years of manual effort from clinicians.\n\nThe advantages of this AI-driven approach span beyond aortic valve replacements, extending to various healthcare challenges. Identifying patients suitable for clinical trials, addressing care gaps in cardiology and oncology, and populating clinical registries are just a few examples. The potential of Dyania Health's Synapsis AI to draw insights from medical records remains vast, promising enhanced outcomes and personalized care for patients.",
  "summary": "From pediatric research to smart hospitals, AI is helping care teams spend less time on routine tasks and more time with patients. Health systems and startups are putting it to work across healthcare, from matching patients to clinical trials to supporting radiologists, hospital teams and patients at home. Clinicians stay at the center, reviewing AI […]",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}