Project description
Thermography AI for early detection of peripheral arterial disease
Peripheral arterial disease (PAD) affects more than 230 million people worldwide, with half of them remaining asymptomatic and receiving late diagnoses. Recent advancements in thermography and AI offer the potential for continuous and preventive healthcare. Kelvin Health has developed a system that employs thermography AI for non-invasive PAD screening, using deep neural networks. A thermal camera generates and analyses thermograms to identify vascular anomalies. The EU-funded AI-CARE project has the following objectives: to address challenges in establishing a clear regulatory pathway for market approval in its initial target markets, design a clinical validation study, evaluate the patentability of the method, and promote women’s entrepreneurship, particularly in the field of deep tech healthcare, where women are significantly underrepresented.
Objective
It is estimated that more than 230M people worldwide suffer from Peripheral Arterial Disease (PAD) and each year more than 22M of them develop Critical Limb Ischemia - a life-threatening condition with 50% combined incidence of amputation and/or death in a 3-year period. Timely PAD diagnosis is the most important factor to avoid complications by treatment procedures (revascularization) and proper disease management (daily walks, change of dietary habits, etc.). Unfortunately, half of the PAD-suffering population is asymptomatic and therefore lately diagnosed. Recent technology advancements in Thermography (portable, high-resolution and precise hardware) and Artificial Intelligence (scalable infrastructure and highly accurate computer vision analysis) can support much needed progress towards continuous and preventive and value-based healthcare.
Kelvin Health develops a clinical decision support system based on Thermography AI for non-invasive, cost-efficient population-wide screening and diagnosis, initially addressing pathology related to PAD - blockage or narrowing of limbs’ blood vessels. The system applies a portable thermal imaging camera that captures body thermodynamics and generates a series of thermograms, which are then thermally segmented, and analyzed temporarily using AI image recognition algorithms. The ML model is trained to detect anomalies related to the vascular system using state-of-the-art machine learning algorithms such as deep neural networks and, in particular convolutional neural networks.
AI-CARE proposal aims at addressing the challenges we meet to structure clear regulatory pathway for market approval at initial target markets, design a clinical validation study and assess the patentability of our method. At the same time promoting women entrepreneurship, especially in deep tech healthcare where women are highly underrepresented. Successful project implementation will lead to Kelvin Health's success in R&D capital fundraising.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- social scienceseconomics and businessbusiness and managemententrepreneurship
- natural sciencesphysical sciencesthermodynamics
- medical and health sciencesbasic medicinepathology
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Keywords
Programme(s)
- HORIZON.3.2 - European innovation ecosystems Main Programme
Funding Scheme
HORIZON-CSA - HORIZON Coordination and Support ActionsCoordinator
1407 Sofia
Bulgaria
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.