{
  "id": 18479,
  "url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1884843",
  "title": "Automated evaluation of dental cavity preparation quality using deep learning and anatomically informed geometric analysis",
  "summary": "BackgroundThe quality of cavity preparation critically influences the longevity and success of restorative dental treatments. Current assessment methods remain largely subjective, relying on visual inspection and examiner judgment, which are prone to variability and limited reproducibility. Although three-dimensional (3D) imaging enables quantitative evaluation, its routine use in clinical and educational settings is limited by cost, accessibility, and workflow complexity.ObjectiveThis study aim",
  "authors": "Abdullah F. Alshammari",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T00:00:00.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "source_slug": "x-frontiers-in-artificial-intelligence",
  "source_name": "Frontiers in Artificial Intelligence",
  "source_homepage": "https://www.frontiersin.org/journals/artificial-intelligence",
  "ethics_ai_record_url": "https://ethics.ai/record/18479",
  "original_url": "https://www.frontiersin.org/articles/10.3389/frai.2026.1884843",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}