Unlocking Early Detection with AI for Amyloid Cardiomyopathy (ATTR-CM)

How can AI help overcome diagnostic challenges in ATTR-CM?

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Harnessing the Power of AI at the Point of Care

AI offers hope in overcoming the challenges associated with ATTR-CM diagnosis. Trained on vast datasets of ECG and echocardiogram tests, AI algorithms can detect subtle patterns indicative of ATTR-CM, facilitating early diagnosis even before significant symptoms appear. By capturing cues imperceptible to the human eye, AI prompts clinicians to determine the next best action. Appropriate workup and treatment is a critical step in preventing disease progression and improving patient outcomes.

  • Early and accurate detection for timely diagnosis and personalized treatment strategies
  • Healthcare equity to expand access to high-quality care for all patients, regardless of their background or location
  • Seamless integration into existing workflows at the point of care to streamline the patient journey

Viz™ Cardio Suite: Revolutionizing Cardiac Care

Equipped with FDA-cleared algorithms, integrated imaging viewers for ECG, echo, and MRI, seamless EHR integration, and robust care team communication tools, the Viz Cardio Suite provides a comprehensive solution for streamlined cardiac disease management.

HCPs review patients with ECGs with suspected ATTR-CM findings, highlighted in green

HCPs gain access to multiple ECGs for patients flagged with suspected ATTR-CM

HCPs seamlessly navigate echocardiograms alongside ECGs for a comprehensive diagnostic overview

Case Study: Streamlining the Hypertrophic Cardiomyopathy (HCM) Patient Journey

Accelerating time to action with Viz.ai in <10 clinical workflow steps

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