Scientific Credibility
Exploring the robust, multi-layered Directed Acyclic Graph (DAG) pipeline that powers our instant predictive oral health metrics.
Pipeline DAG Monitor
Pipeline DAG Model Architecture
Validating focal distance, lighting parameters, and camera alignment parameters on-device before processing. This ensures the source data is clean, blur-free, and clinically structured for inference.
Multi-class segmentation separating crowns, mucosal tissue, gingival margins, and dental restorations. This divides the oral scan into distinct spatial regions for deep analysis.
Locating individual teeth and matching them to standard anatomical dental chart notations (FDI World Dental Federation system). Allows tracking individual teeth longitudinally over multiple scans.
Screening for microscopic structural abrasion, dentin exposure, and mineral loss patterns. Flags areas exhibiting abnormal mechanical wear or chemical erosion.
Analysing localised gingival redness, swelling levels, and margins to detect recession indicators. Allows tracking early signs of periodontal inflammation.
Screening enamel surface density variations and highlighting suspect demineralised areas. Focuses on early cavity identification before decay reaches deeper layers.
Computing the consolidated 0-100 Oral Health Score and generating proactive wellness insights. Compiles structural, hygiene, and risk data into a single, understandable score.
Data Governance
Your privacy and data safety are foundational to our architectural design decisions.
We treat your health data with the highest sensitivity. Every image uploaded to our server is completely anonymised, stripped of metadata, and protected by enterprise-grade end-to-end encryption.
The operational ecosystem is engineered to strictly maintain data privacy requirements (fully GDPR compliance framework).
Governance Board
Our models are continuously supervised, trained, and structurally audited by a seasoned network of dental clinical advisors, dental nursing veterans, and senior artificial intelligence research engineers.
Supervision & Audit
Practicing dental experts validating diagnostic dataset labeling and auditing clinical boundaries of predictive model recommendations.
Protocol Enablement
Seasoned clinical support nurses mapping workflow optimisation, patient education language, and triaging safety guidelines.
Model Architecture
Computer vision specialists training multi-layered neural networks and deploying optimised edge pipeline classifiers.
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