The efficiency of artificial intelligence methods for finding radiographic features in different endodontic treatments - a systematic review.

Abstract

Authors

• Shaqayeq Ramezanzade
  Department of Cariology and Endodontics, Section for Clinical Oral Microbiology, Faculty of Health and Medical Sciences, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.
• Tudor Laurentiu
  Department of Computer Science, University of Copenhagen, Copenhagen, Denmark.
• Azam Bakhshandah
  Department of Cariology and Endodontics, Section for Clinical Oral Microbiology, Faculty of Health and Medical Sciences, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.
• Bulat Ibragimov
  Department of Radiation Oncology, Stanford University School of Medicine, Stanford, California, 94305, USA.
• Thomas Kvist
  Department of Endodontology, Institute of Odontology, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
• Lars Bjørndal
  Department of Cariology and Endodontics, Section for Clinical Oral Microbiology, Faculty of Health and Medical Sciences, Department of Odontology, University of Copenhagen, Copenhagen, Denmark.

Keywords

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