If you are a software developer dealing with the lack of standardized heart failure screening — this project developed an AI-based Decision Support System that integrates voice biomarkers and clinical data to automate risk stratification.
AI-Powered Early Detection and Risk Management System for Heart Failure
Imagine a smart health assistant that catches heart problems before they become emergencies. It looks at everything from your medical records to the sound of your voice to predict if your heart is failing. It's like having a specialist's expertise built into an app for every family doctor and patient.
What needed solving
Heart failure diagnosis is currently slow and relies too heavily on individual doctor expertise, leading to missed treatment windows and high hospital costs.
What was built
An AI-based Decision Support System (DSS) for risk stratification and diagnosis, accompanied by a patient-facing mobile app.
Who needs this
Who can put this to work
If you are a clinic manager dealing with high rates of unnecessary specialist referrals — this project developed a tool for primary care that predicts disease progression, reducing the burden on secondary care.
If you are a device maker dealing with a need for smarter patient monitoring — this project developed a mobile app and AI backend that allows patients to manage their own risks and adhere to prevention strategies.
Quick answers
What is the cost or pricing model for the system?
Based on available project data, specific pricing or cost details are not provided.
Can this be scaled to an industrial level?
Yes, the project aims to reach TRL 8, meaning it is designed for a commercial-ready environment across primary and secondary care in Europe.
How is the IP or licensing handled?
Based on available project data, specific licensing terms are not mentioned, but the system is being developed as a medical class 2b device.
What regulatory standards must it meet?
The system is being developed to meet the requirements of a medical class 2b device.
What is the implementation timeline?
The project runs from 2023-06-01 to 2027-05-31, with the goal of reaching TRL 8 by the end of this period.
Who built it
The consortium is well-balanced for commercialization, featuring 19 partners across 9 countries. With a 26% industry ratio (5 companies, including 3 SMEs), there is a strong bridge between the 8 universities and the market. The inclusion of regulatory and health technology experts ensures the product is designed for certification as a class 2b medical device.
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Contact us to explore licensing opportunities for this AI-based heart failure DSS.