Evaluation of tooth development stages with deep learning-based artificial intelligence algorithm.

Journal: BMC oral health
PMID: 39227802

Abstract

BACKGROUND: This study aims to evaluate the performance of a deep learning system for the evaluation of tooth development stages on images obtained from panoramic radiographs from child patients.

Authors

  • Ayça Kurt
    Faculty of Dentistry, Department of Pediatric Dentistry, Recep Tayyip Erdogan University, Rize, Turkey. ayca.kurt@erdogan.edu.tr.
  • Dilara Nil Gunacar
    Faculty of Dentistry, Department of Oral and Maxillofacial Radiology, Recep Tayyip Erdoğan University, Rize, Turkey.
  • Fatma Yanık Şılbır
    Faculty of Dentistry, Department of Pediatric Dentistry, Recep Tayyip Erdogan University, Rize, Turkey.
  • Zeynep Yeşil
    Faculty of Dentistry, Department of Prosthetic Dentistry, Recep Tayyip Erdogan University, Rize, Turkey.
  • İbrahim Şevki Bayrakdar
    Department of Oral Diagnosis and Radiology, Faculty of Dentistry, Eskişehir Osmangazi University, Eskişehir, Turkey.
  • Özer Çelik
    Department of Mathematics and Computer, Faculty of Science and Letters, Eskişehir Osmangazi University, Eskişehir, Turkey.
  • Elif Bilgir
    Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Eskisehir Osmangazi University, Eskisehir, Turkey.
  • Kaan Orhan
    Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Dentomaxillofacial Radiologist, Ankara University, Ankara, Turkey.

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