Diagnostic capability of artificial intelligence tools for detecting and classifying odontogenic cysts and tumors: a systematic review and meta-analysis.

Journal: Oral surgery, oral medicine, oral pathology and oral radiology
PMID: 38845306

Abstract

OBJECTIVE: To evaluate the diagnostic capability of artificial intelligence (AI) for detecting and classifying odontogenic cysts and tumors, with special emphasis on odontogenic keratocyst (OKC) and ameloblastoma.

Authors

  • Renata Santos Fedato Tobias
    Graduate Program, School of Dentistry, Federal University of Goias, Goiânia, Goiás, Brazil.
  • Ana Beatriz Teodoro
    Graduate Program, School of Dentistry, Federal University of Goias, Goiânia, Goiás, Brazil.
  • Karine Evangelista
  • André Ferreira Leite
    Department of Dentistry, Faculty of Health Sciences, University of Brasília, Brasília, 70910-900, Brazil.
  • Jose Valladares-Neto
  • Brunno Santos de Freitas Silva
    Department of Stomatology, School of Dentistry, Federal University of Goiás, Avenida Universitária esquina com 1a Avenida, Goiânia, S/N. Zip Code: 74605-220, Brazil.
  • Fernanda Paula Yamamoto-Silva
    Department of Stomatology, School of Dentistry, Federal University of Goiás, Avenida Universitária esquina com 1a Avenida, Goiânia, S/N. Zip Code: 74605-220, Brazil.
  • Fabiana T Almeida
    School of Dentistry, Faculty of Medicine and Dentistry, University of Alberta, Canada. Electronic address: fabiana@ualberta.ca.
  • Maria Alves Garcia Silva
    School of Dentistry, Federal University of Goiás, Goiânia, GO, Brazil.

Keywords

External Resources

Popular Topics
Recent Journals