The effect of a deep-learning tool on dentists’ performances in detecting apical radiolucencies on periapical radiographs

Evaluation of artificial intelligence for detecting periapical pathosis on cone‐beam computed tomography scans

(2020) K. Orhan et al.   INTERNATIONAL ENDODONTIC JOURNAL

Artificial Intelligence for the Computer-aided Detection of Periapical Lesions in Cone-beam Computed Tomographic Images

(2020) Frank C. Setzer et al.   JOURNAL OF ENDODONTICS

Development of a Deep Learning Algorithm for Periapical Disease Detection in Dental Radiographs

(2020) Michael G. Endres et al.   Diagnostics

Occurrence of the potent mutagens 2- nitrobenzanthrone and 3-nitrobenzanthrone in fine airborne particles

(2019) Aldenor G. Santos et al.   Scientific Reports

Tooth detection and numbering in panoramic radiographs using convolutional neural networks

(2019) Dmitry V. Tuzoff et al.   DENTOMAXILLOFACIAL RADIOLOGY

Deep Learning for the Radiographic Detection of Apical Lesions

(2019) Thomas Ekert et al.   JOURNAL OF ENDODONTICS

Deep Learning for the Radiographic Detection of Periodontal Bone Loss

(2019) Joachim Krois et al.   Scientific Reports

Evaluation of an artificial intelligence system for detecting vertical root fracture on panoramic radiography

(2019) Motoki Fukuda et al.   Oral Radiology

Diagnosis of cystic lesions using panoramic and cone beam computed tomographic images based on deep learning neural network

(2019) Jae‐Hong Lee et al.   ORAL DISEASES

A deep-learning artificial intelligence system for assessment of root morphology of the mandibular first molar on panoramic radiography

(2018) Teruhiko Hiraiwa et al.   DENTOMAXILLOFACIAL RADIOLOGY

Accuracy of Orthopantomography for Apical Periodontitis without Endodontic Treatment

(2017) Cosimo Nardi et al.   JOURNAL OF ENDODONTICS

Deep Learning: A Primer for Radiologists

(2017) Gabriel Chartrand et al.   RADIOGRAPHICS

From Images to Actions: Opportunities for Artificial Intelligence in Radiology

(2017) Charles E. Kahn   RADIOLOGY

Designing of a Computer Software for Detection of Approximal Caries in Posterior Teeth

(2015) Solmaz Valizadeh et al.   Iranian Journal of Radiology

Deep learning

(2015) Yann LeCun et al.   NATURE

Evaluating the Periapical Status of Teeth with Irreversible Pulpitis by Using Cone-beam Computed Tomography Scanning and Periapical Radiographs

(2012) Francesc Abella et al.   JOURNAL OF ENDODONTICS

Chapter 9: Options for Summarizing Medical Test Performance in the Absence of a “Gold Standard”

(2012) Thomas A. Trikalinos et al.   JOURNAL OF GENERAL INTERNAL MEDICINE

Artificial Neural Network Modeling for Deciding if Extractions Are Necessary Prior to Orthodontic Treatment

(2009) Xiaoqiu Xie et al.   ANGLE ORTHODONTIST

Effect of computer assistance on observer performance of approximal caries diagnosis using intraoral digital radiography

(2009) Kazuyuki Araki et al.   Clinical Oral Investigations

Detection of periapical bone defects in human jaws using cone beam computed tomography and intraoral radiography

(2009) S. Patel et al.   INTERNATIONAL ENDODONTIC JOURNAL

Recent Developments in the Dorfman-Berbaum-Metz Procedure for Multireader ROC Study Analysis

(2008) Stephen L. Hillis et al.   ACADEMIC RADIOLOGY

Comparison of Periapical Radiography and Limited Cone-Beam Tomography in Posterior Maxillary Teeth Referred for Apical Surgery

(2008) Kenneth M.T. Low et al.   JOURNAL OF ENDODONTICS

Accuracy of Cone Beam Computed Tomography and Panoramic and Periapical Radiography for Detection of Apical Periodontitis

(2008) Carlos Estrela et al.   JOURNAL OF ENDODONTICS