Summary
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.
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.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/101113791 |
| Start date: | 01-07-2023 |
| End date: | 29-02-2024 |
| Total budget - Public funding: | - 75 000,00 Euro |
Cordis data
Original description
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.
Status
SIGNEDCall topic
HORIZON-EIE-2022-SCALEUP-02-02Update Date
31-07-2023
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