AIdentifyAGE Ontology for Decision Support in Forensic Dental Age Assessment
New ontology tackles fragmented data and AI opacity in critical legal cases involving minors.
Deep Dive
A team led by Cátia Vaz and Renato Marcelo developed the AIdentifyAGE ontology, a standardized framework for forensic dental age assessment. It integrates judicial context, dental exams, radiographic imaging, and AI-based estimation methods into a single, semantically coherent model. Built on established biomedical and machine learning ontologies, it ensures FAIR principles and interoperability. This provides a foundation for transparent, explainable, and reproducible decision-support systems in medico-legal contexts.
Why It Matters
It brings consistency and auditability to age assessments that determine legal rights and protection for undocumented individuals.