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<p>Integrating deep learning into healthcare enables personalized care but raises trust issues due to model opacity. To improve transparency, we propose a system for dental age estimation from panoramic images that combines an opaque and a transparent method within a Natural Language Generation module. This module generates clinician-friendly textual explanations of age estimations, designed with dental experts through a rule-based approach. Following the best practices in the field, the quality of the generated explanations was manually validated by human experts using a questionnaire. The results showed a strong performance, since the experts rated 4.77±0.12 (out of 5) on average across the five dimensions considered. We also performed a trustworthy self-assessment procedure following the Assessment List for Trustworthy Artificial Intelligence checklist, in which it scored 4.40±0.27 (out of 5) across its seven dimensions.</p>

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Trustworthy Data-driven Chronological Age Estimation from Panoramic Dental Images

  • 期刊论文

  • 发表日期：

    2026年1月15日

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  • Ainhoa Vivel-Couso,
  • Nicolás Vila-Blanco,
  • María J. Carreira,
  • Alberto Bugarín-Diz,
  • Inmaculada Tomás,
  • Jose M. Alonso-Moral

摘要

Integrating deep learning into healthcare enables personalized care but raises trust issues due to model opacity. To improve transparency, we propose a system for dental age estimation from panoramic images that combines an opaque and a transparent method within a Natural Language Generation module. This module generates clinician-friendly textual explanations of age estimations, designed with dental experts through a rule-based approach. Following the best practices in the field, the quality of the generated explanations was manually validated by human experts using a questionnaire. The results showed a strong performance, since the experts rated 4.77±0.12 (out of 5) on average across the five dimensions considered. We also performed a trustworthy self-assessment procedure following the Assessment List for Trustworthy Artificial Intelligence checklist, in which it scored 4.40±0.27 (out of 5) across its seven dimensions.