Evidence map›Paper›PMID 42346902›Full record

ArticleJournal of imaging2026

A Pilot Study on AI-Driven Age Estimation and Sex Determination in Greek Individuals.

Anastasia Mitsea, Nikolaos Christoloukas, Aliki Rontogianni, Marko Subašić, Denis Milošević, Marin Vodanović

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Article in Journal of imaging, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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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.

2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

6 authors.

Anastasia MitseaDepartment of Oral Diagnosis and Radiology, Dental School, National and Kapodistrian University of Athens (NKUA), 11527 Athens, Greece.ORCID 0000-0003-2833-681X
Nikolaos ChristoloukasDepartment of Oral Diagnosis and Radiology, Dental School, National and Kapodistrian University of Athens (NKUA), 11527 Athens, Greece.ORCID 0009-0004-3530-2639
Aliki RontogianniDivision of Dental Technology, Department of Biomedical Sciences, University of West Attica, 12243 Athens, Greece.ORCID 0000-0003-0218-2963
Marko SubašićFaculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-4321-4557
Denis MiloševićFaculty of Electrical Engineering and Computing, University of Zagreb, 10000 Zagreb, Croatia.
Marin VodanovićDepartment of Dental Anthropology, School of Dental Medicine, University of Zagreb, 10000 Zagreb, Croatia.ORCID 0000-0002-1935-8657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

AI methods (machine learning and deep learning methods) presented promising results concerning the accuracy of dental age estimation and sex determination. Therefore, this pilot study aims to evaluate the efficacy of an artificial intelligence system to estimate age and determine sex in a Greek population sample. Panoramic radiographs from 110 adult subjects comprised this study's sample. Males and females were equally distributed (1/1) in the sample. The dental status of each patient was different. The sample's age ranged from 9 to 84 years of age, with a mean age of 48.87 years (±16.14 yrs). The methodology employed beta versions of convolutional neural networks (CNNs) developed by the University of Zagreb. Separate CNNs were trained on 4000 panoramic radiographs: one for sex estimation and another for age estimation. The AI program overestimated the subjects' age on average by 4.16 years. A statistically significant correlation was found between true and estimated sex (

Indexed as

AIdental age estimationgender determinationsex determination

Identifiers

PMID42346902
PMCPMC13301963

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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.