Deep learning-designed implant-supported posterior crowns: Assessing time efficiency, tooth morphology, emergence profile, occlusion, and proximal contacts.

Journal: Journal of dentistry
PMID: 38906454

Abstract

OBJECTIVES: To compare implant supported crowns (ISCs) designed using deep learning (DL) software with those designed by a technician using conventional computer-aided design software.

Authors

  • Jun-Ho Cho
    Department of Prosthodontics, Seoul National University Dental Hospital, Seoul, Republic of Korea.
  • Gülce Çakmak
    Department of Reconstructive Dentistry and Gerodontology, School of Dental Medicine, University of Bern, Bern, Switzerland.
  • Jinhyeok Choi
    PhD Candidate, Department of Biomedical Sciences, Seoul National University, Seoul, Republic of Korea.
  • Dongwook Lee
  • Hyung-In Yoon
    Department of Reconstructive Dentistry and Gerodontology, School of Dental Medicine, University of Bern, Bern, Switzerland; Department of Prosthodontics, School of Dentistry and Dental Research Institute, Seoul National University, Seoul, Republic of Korea. Electronic address: drhiy226@snu.ac.kr.
  • Burak Yilmaz
    Department of Reconstructive Dentistry and Gerodontology, School of Dental Medicine, University of Bern, Bern, Switzerland; Department of Restorative, Preventive and Pediatric Dentistry, School of Dental Medicine, University of Bern, Bern, Switzerland; Division of Restorative and Prosthetic Dentistry, The Ohio State University, Columbus, OH, USA.
  • Martin Schimmel
    Department of Reconstructive Dentistry and Gerodontology, School of Dental Medicine, University of Bern, Bern, Switzerland.

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