Devices

PocketECG

AI-driven ambulatory ECG monitoring for real-time arrhythmia detection, full disclosure data, and rich diagnostic reports.

Kardiobeat.ai

Wearable ECG monitor that combines long-term recording with AI-driven analysis for efficient arrhythmia diagnosis.

AI & Software Platform

DeepRhythmAI (DRAI)

FDA-Cleared AI algorithms that detect and classify arrhythmias quickly across third-party software and devices.

 

DeepRhythm Platform (DRP)

AI-powered cloud ECG platform for accurate arrhythmia detection, analysis, and reporting across multiple devices.

Advanced Diagnostics

Virtual Cardiac Stress Test (VCAST)

Advanced CT-based cardiac diagnostics software for assessing the hemodynamic significance of coronary lesions.

Clinical Trials

AI-powered ECG monitoring solutions for clinical trials focused on cardiac safety, compliance, and data accuracy.

Research and Developments

Medical technology R&D focused on AI, cardiovascular disease diagnosis, and next-generation diagnostic solutions.

VCAST

An AI-powered, non-invasive alternative to stress tests and invasive angiography

The Virtual Cardiac Stress Test (VCAST) is a patented, AI-based medical system developed for non-invasive, clinical quantitative and qualitative analysis of CT-scan data, to assess the hemodynamic significance of coronary artery atherosclerotic stenosis.

The Virtual Cardiac Stress (VCAST) is a patented medical system developed by Kardiolytics to assess the hemodynamic significance of coronary artery atherosclerotic stenosis. It delivers detailed, real-time visualizations of coronary anatomy and flow dynamics, including computed quantities of blood, pressure, and velocity to assist physicians in completing the diagnosis and designing the treatment plan for coronary artery disease.
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FFR Insights from a Simple CT Scan

The Virtual Cardiac Stress Test (VCAST) is a patented, AI-based medical system developed for non-invasive, clinical quantitative and qualitative analysis of CT-scan data, to assess the hemodynamic significance of coronary artery atherosclerotic stenosis.

All data that are required for VCAST come from a widely available and inexpensive CT-scan imaging that is conducted by a technician and not a doctor and the results can be forwarded to a doctor remotely. It is independent of imaging equipment, imaging protocols, and equipment vendors.

01

CT Scan

02

CT Dataset

03

AI Power

Vessel segmentation and reconstruction

04

Full Analysis

05

Results

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Advantages of VCAST

VCAST provides a safe, accessible, and cost-effective alternative to traditional FFR diagnostics—using only standard CT imaging, without wires, catheters, or specialist intervention.

  • Offers non-invasive assessment of the hemodynamic significance of coronary artery atherosclerotic lesions, therefore, imposing no risk, cost, and availability problems involved in the traditional FFR diagnostics (which include inserting a pressure wire into coronary arteries)
  • Involves no additional, significant radiation exposure related to inserting a pressure wire into coronary arteries
  • Uses AI and Big Data Learning methods to segment, reconstruct, and predict hemodynamic index and changes in flow rate, heart rate, and degree of stenosis
  • Offers personalized models of coronary vessel anatomy including highly informative for the physician, 3D imaging of blood vessels
  • Offers advanced risk analysis of the progression of coronary stenosis
  • Offers personalized planning, simulation, and prediction of the personalized effects of revascularization
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This is a medical device. Use it according to the instruction manual or label. The manufacturer and entity advertising is Medicalgorithmics S.A.

Kardiolytics Virtual Cardiac Stress Test (VCAST) is software for simulating coronary vessel physiology for clinical quantitative and qualitative analysis of previously acquired data from computer tomography in DICOM format, specifically for clinically stable, symptomatic patients with coronary artery disease.

See also

PocketECG
VCAST
Kardiobeat.ai
DRAI
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Kardiobeat

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PocketECG

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PocketECG

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DeepRhythm Platform (DRP)

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The wait is almost over!

DRAI MARTINI study is set to be published soon. Be the first to know when it lands.
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DeepRhythmAI (DRAI)

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