Objective
"Cliniccards AI: Deep Tech Revolution in 3D Dental Diagnostics
Radiology accounts for 82% of all diagnostic errors in medicine, with practitioners missing up to 44% of pathologies due to fatigue and physiological limitations. Manual analysis of a single 3D scan (CBCT) takes 15–20 minutes, creating a critical bottleneck amidst a global staff shortage. Furthermore, the current market is compromised by non-GDPR compliant solutions with Russian origins, creating unacceptable data security risks for EU clinics.
Cliniccards AI is the first fully GDPR-compliant ""Clean AI"" cloud platform for automated 3D segmentation and diagnostics. Unlike competitors relying on 2D projections, we utilize a True 3D Voxel-based approach (proprietary 3D CNN/U-Net architectures) to analyze volumetric data. The solution integrates seamlessly into the Cliniccards ERP ecosystem, already used by 4,700+ clinics, ensuring instant market access.
Key Innovations:
1. Data Moat: We possess the largest verified private dataset in Eastern Europe (240,000 CT scans), creating an uncopyable advantage for training Deep Learning models.
2. Technological Gap: We solve the ""blind spots"" of existing AI by implementing Metal Artifact Reduction (MAR) and full segmentation of nerves and sinuses directly in voxel space.
3. Digital Sovereignty: We provide a secure European alternative, ensuring data never leaves safe jurisdictions.
Measurable Objectives (TRL 4 → TRL 7) Over 24 months, we aim to achieve:
- Diagnostic Excellence: Sensitivity >97.3% for pathologies and >95% segmentation accuracy (IoU) for critical anatomy.
- Efficiency: Reducing analysis time from 20 minutes to 2–5 seconds (150x faster).
- Commercial Impact: Validating a >20% increase in Case Acceptance Rates via pilot testing and securing MDR Class IIa readiness.
Action Plan The project involves finalizing R&D (specifically for artifact reduction), conducting a 3-phase ""Living Lab"" clinical trial in 50 clinics, and filing 4 patent applications"
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. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences computer and information sciences computer security data protection
- engineering and technology medical engineering diagnostic imaging computed tomography
- medical and health sciences clinical medicine radiology
- medical and health sciences basic medicine pathology
- natural sciences computer and information sciences artificial intelligence machine learning deep learning
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.3.1 - The European Innovation Council (EIC)
MAIN PROGRAMME
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HORIZON.3.1.3 - Additional EIC activities
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-EIC - HORIZON EIC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-EIC-2025-UKRAINIANTECH-01
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
04119 Kyiv
Ukraine
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.