The startup develops cloud-based artificial intelligence software for cardiac data analysis, utilizing proprietary algorithms validated against arrhythmia and clinical datasets. This technology provides healthcare providers with clear, actionable reports that enhance diagnostic accuracy and streamline clinical workflows.
Funding
$3.5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Cardiac data analysis, particularly of long-term ECG recordings, is often time-consuming and requires specialized expertise, potentially leading to delays in diagnosis and treatment. Traditional methods can be inefficient, limiting the number of patients that can be comprehensively assessed and increasing the risk of inaccurate analysis due to human error.
Solution
Cardiomatics offers a cloud-based platform that leverages artificial intelligence to automate and streamline long-term ECG analysis. The platform ingests raw ECG signals from Holter monitors, ECG patches, and other devices, then applies deep neural network algorithms to identify anomalies and generate comprehensive reports. These reports are accessible through an intuitive web application, providing clinicians with actionable insights to support faster and more accurate diagnoses. By automating the analysis process, Cardiomatics reduces analysis time, improves diagnostic accuracy, and enables cardiac clinics and service providers to scale their ECG services efficiently.
Target Audience
The primary target audience includes cardiologists, cardiac clinics, and service providers seeking to improve the efficiency and accuracy of their ECG analysis workflows.
Features
- AI-powered analysis of long-term ECG recordings, reducing analysis time by up to 80%
- Device-independent platform compatible with over 40 Holter and ECG patch models
- Cloud-based platform accessible via web application, requiring no on-site installation
- Interactive reports with comprehensive anomaly detection
- Algorithms trained on a large dataset of real-world ECGs
- Compliant with data safety standards and certified as a medical device