Determining the reliability of diagnosis and treatment using artificial intelligence software with panoramic radiographs-Reference-Cited by-同舟云学术

Determining the reliability of diagnosis and treatment using artificial intelligence software with panoramic radiographs

Published:2023 Issue:3 Volume:53 Page:199
ISSN:2233-7822
Container-title:Imaging Science in Dentistry
language:en
Short-container-title:Imaging Sci Dent

Author:

Orhan Kaan¹^ORCID,Aktuna Belgin Ceren²^ORCID,Manulis David³^ORCID,Golitsyna Maria³^ORCID,Bayrak Seval⁴^ORCID,Aksoy Secil⁵^ORCID,Sanders Alex³^ORCID,Önder Merve¹^ORCID,Ezhov Matvey³^ORCID,Shamshiev Mamat³^ORCID,Gusarev Maxim³^ORCID,Shlenskii Vladislav³^ORCID

Affiliation:

1. Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Ankara University, Ankara, Turkey.

2. Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Hatay Mustafa Kemal University, Hatay, Turkey.

3. Diagnocat Inc., San Francisco, CA, USA.

4. Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Abant İzzet Baysal University, Bolu, Turkey.

5. Department of Dentomaxillofacial Radiology, Faculty of Dentistry, Near East University, Nicosia, Cyprus.

Publisher

XMLink

Subject

Radiology, Nuclear Medicine and imaging,General Dentistry,Radiological and Ultrasound Technology

Link

https://isdent.org/pdf/10.5624/isd.20230109

Reference46 articles.

1. Deep Learning: A Primer for Radiologists

2. The use and performance of artificial intelligence applications in dental and maxillofacial radiology: A systematic review

3. Deep learning beyond cats and dogs: recent advances in diagnosing breast cancer with deep neural networks

4. Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning

5. Artificial intelligence in fracture detection: transfer learning from deep convolutional neural networks

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