Detalhe da pesquisa
1.
A deep learning approach for dental implant planning in cone-beam computed tomography images.
BMC Med Imaging
; 21(1): 86, 2021 05 19.
Artigo
em Inglês
| MEDLINE | ID: mdl-34011314
2.
Assessing the reliability of CBCT-based AI-generated STL files in diagnosing osseous changes of the mandibular condyle: a comparative study with ground truth diagnosis.
Dentomaxillofac Radiol
; 52(7): 20230141, 2023 Oct.
Artigo
em Inglês
| MEDLINE | ID: mdl-37641960
3.
Evaluation of a Decision Support System Developed with Deep Learning Approach for Detecting Dental Caries with Cone-Beam Computed Tomography Imaging.
Diagnostics (Basel)
; 13(22)2023 Nov 18.
Artigo
em Inglês
| MEDLINE | ID: mdl-37998607
4.
Determining the reliability of diagnosis and treatment using artificial intelligence software with panoramic radiographs.
Imaging Sci Dent
; 53(3): 199-208, 2023 Sep.
Artigo
em Inglês
| MEDLINE | ID: mdl-37799743
5.
AI-based automatic segmentation of craniomaxillofacial anatomy from CBCT scans for automatic detection of pharyngeal airway evaluations in OSA patients.
Sci Rep
; 12(1): 11863, 2022 07 13.
Artigo
em Inglês
| MEDLINE | ID: mdl-35831451
6.
Evaluation of artificial intelligence for detecting impacted third molars on cone-beam computed tomography scans.
J Stomatol Oral Maxillofac Surg
; 122(4): 333-337, 2021 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-33346145
7.
Clinically applicable artificial intelligence system for dental diagnosis with CBCT.
Sci Rep
; 11(1): 15006, 2021 07 22.
Artigo
em Inglês
| MEDLINE | ID: mdl-34294759
8.
Author Correction: Clinically applicable artificial intelligence system for dental diagnosis with CBCT.
Sci Rep
; 11(1): 22217, 2021 Nov 09.
Artigo
em Inglês
| MEDLINE | ID: mdl-34754062