Efficacy of the methods of age determination using artificial intelligence in panoramic radiographs - a systematic review.

Journal: International journal of legal medicine
Published Date:

Abstract

The aim of this systematic review is to analyze the literature to determine whether the methods of artificial intelligence are effective in determining age in panoramic radiographs. Searches without language and year limits were conducted in PubMed/Medline, Embase, Web of Science, and Scopus databases. Hand searches were also performed, and unpublished manuscripts were searched in specialized journals. Thirty-six articles were included in the analysis. Significant differences in terms of root mean square error and mean absolute error were found between manual methods and artificial intelligence techniques, favoring the use of artificial intelligence (p < 0.00001). Few articles compared deep learning methods with machine learning models or manual models. Although there are advantages of machine learning in data processing and deep learning in data collection and analysis, non-comparable data was a limitation of this study. More information is needed on the comparison of these techniques, with particular emphasis on time as a variable.

Authors

  • Tania Camila Niño-Sandoval
    Universidad Nacional de Colombia - Bogotá. Faculty of Dentistry, Oral Health Department. Master of Dentistry. Craniofacial Growth and Development Research Group. Genetics Institute, Cll 53 - Cra. 37 Ed. 426 Of. 213. Bogotá Colombia. Electronic address: kotc2578@gmail.com.
  • Ana Milena Doria-Martinez
    Institute National of Legal Medicine and Forensic Sciences, Medellin, Colombia.
  • Ruby Amparo Vásquez Escobar
    Institute National of Legal Medicine and Forensic Sciences, Cali, Colombia.
  • Elizabeth Llano Sánchez
    College of Dentistry, University of Antioquia, Medellin, Colombia.
  • Isabella Bermón Rojas
    Electronic Engineering Faculty, Department of Electronics and Telecommunications, University of Antioquia, Medellin, Colombia.
  • Laura Cristina Vargas Álvarez
    Electronic Engineering Faculty, Department of Electronics and Telecommunications, University of Antioquia, Medellin, Colombia.
  • David Stephen Fernandez Mc Cann
    Electronic Engineering Faculty, Department of Electronics and Telecommunications, University of Antioquia, Medellin, Colombia.
  • Liliana Marcela Támara-Patiño
    National Institute of Legal Medicine and Forensic Sciences, Bogota, Colombia. ltamara@medicinalegal.gov.co.