These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

180 related articles for article (PubMed ID: 36673010)

  • 21. Caries Detection with Near-Infrared Transillumination Using Deep Learning.
    Casalegno F; Newton T; Daher R; Abdelaziz M; Lodi-Rizzini A; Schürmann F; Krejci I; Markram H
    J Dent Res; 2019 Oct; 98(11):1227-1233. PubMed ID: 31449759
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Artificial intelligence for caries detection: a novel diagnostic tool using deep learning algorithms.
    Liu Y; Xia K; Cen Y; Ying S; Zhao Z
    Oral Radiol; 2024 Jul; 40(3):375-384. PubMed ID: 38498223
    [TBL] [Abstract][Full Text] [Related]  

  • 23. An artifıcial ıntelligence approach to automatic tooth detection and numbering in panoramic radiographs.
    Bilgir E; Bayrakdar İŞ; Çelik Ö; Orhan K; Akkoca F; Sağlam H; Odabaş A; Aslan AF; Ozcetin C; Kıllı M; Rozylo-Kalinowska I
    BMC Med Imaging; 2021 Aug; 21(1):124. PubMed ID: 34388975
    [TBL] [Abstract][Full Text] [Related]  

  • 24. A comprehensive artificial intelligence framework for dental diagnosis and charting.
    Kabir T; Lee CT; Chen L; Jiang X; Shams S
    BMC Oral Health; 2022 Nov; 22(1):480. PubMed ID: 36352390
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Context Aware Convolutional Neural Network for Children Caries Diagnosis on Dental Panoramic Radiographs.
    Zhou X; Yu G; Yin Q; Liu Y; Zhang Z; Sun J
    Comput Math Methods Med; 2022; 2022():6029245. PubMed ID: 36188109
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Performance evaluation of a deep learning model for automatic detection and localization of idiopathic osteosclerosis on dental panoramic radiographs.
    Tassoker M; Öziç MÜ; Yuce F
    Sci Rep; 2024 Feb; 14(1):4437. PubMed ID: 38396289
    [TBL] [Abstract][Full Text] [Related]  

  • 27. A Deep Learning Model for Idiopathic Osteosclerosis Detection on Panoramic Radiographs.
    Yesiltepe S; Bayrakdar IS; Orhan K; Çelik Ö; Bilgir E; Aslan AF; Odabaş A; Costa ALF; Jagtap R
    Med Princ Pract; 2022; 31(6):555-561. PubMed ID: 36167054
    [TBL] [Abstract][Full Text] [Related]  

  • 28. AI-Assisted Detection of Interproximal, Occlusal, and Secondary Caries on Bite-Wing Radiographs: A Single-Shot Deep Learning Approach.
    Karakuş R; Öziç MÜ; Tassoker M
    J Imaging Inform Med; 2024 May; ():. PubMed ID: 38743125
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Deep Learning for Diagnostic Charting on Pediatric Panoramic Radiographs.
    Kaya E; Güneç HG; Ürkmez EŞ; Cesur Aydın K; Ateş HF
    Int J Comput Dent; 2023 Jul; 0(0):0. PubMed ID: 37417445
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Application of a fully deep convolutional neural network to the automation of tooth segmentation on panoramic radiographs.
    Lee JH; Han SS; Kim YH; Lee C; Kim I
    Oral Surg Oral Med Oral Pathol Oral Radiol; 2020 Jun; 129(6):635-642. PubMed ID: 31992524
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Caries detection with tooth surface segmentation on intraoral photographic images using deep learning.
    Park EY; Cho H; Kang S; Jeong S; Kim EK
    BMC Oral Health; 2022 Dec; 22(1):573. PubMed ID: 36476359
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Collaborative deep learning model for tooth segmentation and identification using panoramic radiographs.
    Chandrashekar G; AlQarni S; Bumann EE; Lee Y
    Comput Biol Med; 2022 Sep; 148():105829. PubMed ID: 35868047
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Deep Learning for Automated Detection of Cyst and Tumors of the Jaw in Panoramic Radiographs.
    Yang H; Jo E; Kim HJ; Cha IH; Jung YS; Nam W; Kim JY; Kim JK; Kim YH; Oh TG; Han SS; Kim H; Kim D
    J Clin Med; 2020 Jun; 9(6):. PubMed ID: 32545602
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Analysis of the feasibility of using deep learning for multiclass classification of dental anomalies on panoramic radiographs.
    Okazaki S; Mine Y; Iwamoto Y; Urabe S; Mitsuhata C; Nomura R; Kakimoto N; Murayama T
    Dent Mater J; 2022 Nov; 41(6):889-895. PubMed ID: 36002296
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Children's dental panoramic radiographs dataset for caries segmentation and dental disease detection.
    Zhang Y; Ye F; Chen L; Xu F; Chen X; Wu H; Cao M; Li Y; Wang Y; Huang X
    Sci Data; 2023 Jun; 10(1):380. PubMed ID: 37316638
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Artificial intelligence in the detection and classification of dental caries.
    Ahmed WM; Azhari AA; Fawaz KA; Ahmed HM; Alsadah ZM; Majumdar A; Carvalho RM
    J Prosthet Dent; 2023 Aug; ():. PubMed ID: 37640607
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Detection of caries around restorations on bitewings using deep learning.
    Chaves ET; Vinayahalingam S; van Nistelrooij N; Xi T; Romero VHD; Flügge T; Saker H; Kim A; Lima GDS; Loomans B; Huysmans MC; Mendes FM; Cenci MS
    J Dent; 2024 Apr; 143():104886. PubMed ID: 38342368
    [TBL] [Abstract][Full Text] [Related]  

  • 38. The U-Net Approaches to Evaluation of Dental Bite-Wing Radiographs: An Artificial Intelligence Study.
    Baydar O; Różyło-Kalinowska I; Futyma-Gąbka K; Sağlam H
    Diagnostics (Basel); 2023 Jan; 13(3):. PubMed ID: 36766557
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Detecting caries lesions of different radiographic extension on bitewings using deep learning.
    Cantu AG; Gehrung S; Krois J; Chaurasia A; Rossi JG; Gaudin R; Elhennawy K; Schwendicke F
    J Dent; 2020 Sep; 100():103425. PubMed ID: 32634466
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Detection and Segmentation of Radiolucent Lesions in the Lower Jaw on Panoramic Radiographs Using Deep Neural Networks.
    Rašić M; Tropčić M; Karlović P; Gabrić D; Subašić M; Knežević P
    Medicina (Kaunas); 2023 Dec; 59(12):. PubMed ID: 38138241
    [No Abstract]   [Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 9.