Artificial Intelligence‐Driven Automated Design of Anterior and Posterior Crowns Under Diverse Occlusal Scenarios
Automated crown design outcomes depend on occlusal scenarios and CAD software selection. DL-based CAD software demonstrated superior clinical quality, particularly for posterior crowns, indicating higher clinical suitability. However, further software refinement is needed to consistently produce clinically acceptable crowns under diverse occlusal conditions, such as anterior diastemas.
Authors
- Jae‐Hyun Lee (ORCID: https://orcid.org/0000-0002-2631-7722)
- Sung‐Jin Kim
- Duygu Karasan (ORCID: https://orcid.org/0000-0003-4631-2053)
- Irena Sailer (ORCID: https://orcid.org/0000-0002-4537-7624)
- Gülce Çakmak (ORCID: https://orcid.org/0000-0003-1751-9207)
- Nan Hsu Myat Mon Hlaing (ORCID: https://orcid.org/0009-0004-8746-6985)
Institutions
- University of Geneva (CH)
- University of Bern (CH)
- Seoul National University (KR)
- Humboldt-Universität zu Berlin (DE)
- Seoul National University Dental Hospital (KR)
Publication Details
- Journal
- Journal of Esthetic and Restorative Dentistry
- Published
- 2025-09-05
- DOI
- https://doi.org/10.1111/jerd.70029
- Citations
- 3
- Primary Topic
- Dental materials and restorations
- Type
- article
- Field-Weighted Citation Impact
- 5.03
Funders
- Korea Medical Device Development Fund
- National Research Foundation
- Ministry of Food and Drug Safety
- National Research Foundation of Korea
- Ministry of Science and ICT, South Korea