ReviewInternational journal of legal medicine2026
AI decision support in forensic dental age assessment: proposed criteria for living individuals.
Review in International journal of legal medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
3 citing papers in PubMed.
- Review
- Population effects and cross-population generalisability of the third molar maturity index for 18-year age classification: a multi-centre study with machine learning validation.International journal of legal medicine · 2026Article
- Dental age assessment: orthopantomogram-based comparison of traditional methods and artificial intelligence in the adult population.International journal of legal medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
Abstract
Artificial intelligence (AI) has rapidly evolved from a technological innovation to a key instrument in forensic decision-making. Within forensic odontology, AI offers an unprecedented capacity to analyse dental radiographs objectively, reproducibly, and at scale. This opinion paper discusses the integration of AI in forensic dental age assessment, examining its ethical, scientific, and legal implications. Building on established standards—Schmeling’s 2008 recommendations, IOFOS and ABFO guidelines, and EASO protocols for age assessment in asylum procedures—this work explores how AI systems can operate as decision-support tools rather than substitutes for expert judgment. It further outlines how compliance with ISO/TC 106/WG 13 and the forthcoming ISO 18374:2025 standard, together with adherence to the EU Artificial Intelligence Act, enables the development of trustworthy, auditable, and low-risk AI models. Drawing on evidence from oral-health AI research from Schwendicke et al., 2025 and the author’s own forensic studies conducted in Portugal (2015–2025), the paper argues that AI can enhance the credibility and legal admissibility of dental age assessment when implemented within robust ethical and regulatory frameworks.
Indexed as
Identifiers
41612067What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.