BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

285 related articles for article (PubMed ID: 34046742)

  • 21. Artificial intelligence system for automated landmark localization and analysis of cephalometry.
    Jiang F; Guo Y; Yang C; Zhou Y; Lin Y; Cheng F; Quan S; Feng Q; Li J
    Dentomaxillofac Radiol; 2023 Jan; 52(1):20220081. PubMed ID: 36279185
    [TBL] [Abstract][Full Text] [Related]  

  • 22. Automatic localization of cephalometric landmarks based on convolutional neural network.
    Yao J; Zeng W; He T; Zhou S; Zhang Y; Guo J; Tang W
    Am J Orthod Dentofacial Orthop; 2022 Mar; 161(3):e250-e259. PubMed ID: 34802868
    [TBL] [Abstract][Full Text] [Related]  

  • 23. Deep learning for caries detection: A systematic review.
    Mohammad-Rahimi H; Motamedian SR; Rohban MH; Krois J; Uribe SE; Mahmoudinia E; Rokhshad R; Nadimi M; Schwendicke F
    J Dent; 2022 Jul; 122():104115. PubMed ID: 35367318
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Automatic identification of posteroanterior cephalometric landmarks using a novel deep learning algorithm: a comparative study with human experts.
    Lee H; Cho JM; Ryu S; Ryu S; Chang E; Jung YS; Kim JY
    Sci Rep; 2023 Sep; 13(1):15506. PubMed ID: 37726392
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Automatic cephalometric landmark identification with artificial intelligence: An umbrella review of systematic reviews.
    Polizzi A; Leonardi R
    J Dent; 2024 Jul; 146():105056. PubMed ID: 38729291
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Performance of a Convolutional Neural Network- Based Artificial Intelligence Algorithm for Automatic Cephalometric Landmark Detection.
    Uğurlu M
    Turk J Orthod; 2022 Jun; 35(2):94-100. PubMed ID: 35788433
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Automated identification of cephalometric landmarks:
    Hwang HW; Park JH; Moon JH; Yu Y; Kim H; Her SB; Srinivasan G; Aljanabi MNA; Donatelli RE; Lee SJ
    Angle Orthod; 2020 Jan; 90(1):69-76. PubMed ID: 31335162
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Web-based fully automated cephalometric analysis by deep learning.
    Kim H; Shim E; Park J; Kim YJ; Lee U; Kim Y
    Comput Methods Programs Biomed; 2020 Oct; 194():105513. PubMed ID: 32403052
    [TBL] [Abstract][Full Text] [Related]  

  • 29. An automatic cephalometric landmark detection method based on heatmap regression and Monte Carlo dropout.
    Chen J; Che H; Sun J; Rao Y; Wu J
    Annu Int Conf IEEE Eng Med Biol Soc; 2023 Jul; 2023():1-4. PubMed ID: 38083204
    [TBL] [Abstract][Full Text] [Related]  

  • 30. A fully deep learning model for the automatic identification of cephalometric landmarks.
    Kim YH; Lee C; Ha EG; Choi YJ; Han SS
    Imaging Sci Dent; 2021 Sep; 51(3):299-306. PubMed ID: 34621657
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Cascaded convolutional networks for automatic cephalometric landmark detection.
    Zeng M; Yan Z; Liu S; Zhou Y; Qiu L
    Med Image Anal; 2021 Feb; 68():101904. PubMed ID: 33290934
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Accuracy and reliability of automatic three-dimensional cephalometric landmarking.
    Dot G; Rafflenbeul F; Arbotto M; Gajny L; Rouch P; Schouman T
    Int J Oral Maxillofac Surg; 2020 Oct; 49(10):1367-1378. PubMed ID: 32169306
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Effectiveness of Human-Artificial Intelligence Collaboration in Cephalometric Landmark Detection.
    Le VNT; Kang J; Oh IS; Kim JG; Yang YM; Lee DW
    J Pers Med; 2022 Mar; 12(3):. PubMed ID: 35330386
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Cephalometric landmark detection without X-rays combining coordinate regression and heatmap regression.
    Takahashi K; Shimamura Y; Tachiki C; Nishii Y; Hagiwara M
    Sci Rep; 2023 Nov; 13(1):20011. PubMed ID: 37974018
    [TBL] [Abstract][Full Text] [Related]  

  • 35. Evaluation of automated cephalometric analysis based on the latest deep learning method.
    Hwang HW; Moon JH; Kim MG; Donatelli RE; Lee SJ
    Angle Orthod; 2021 May; 91(3):329-335. PubMed ID: 33434275
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Application of Artificial Intelligence (AI) in a Cephalometric Analysis: A Narrative Review.
    Kiełczykowski M; Kamiński K; Perkowski K; Zadurska M; Czochrowska E
    Diagnostics (Basel); 2023 Aug; 13(16):. PubMed ID: 37627899
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Development, Application, and Performance of Artificial Intelligence in Cephalometric Landmark Identification and Diagnosis: A Systematic Review.
    Junaid N; Khan N; Ahmed N; Abbasi MS; Das G; Maqsood A; Ahmed AR; Marya A; Alam MK; Heboyan A
    Healthcare (Basel); 2022 Dec; 10(12):. PubMed ID: 36553978
    [TBL] [Abstract][Full Text] [Related]  

  • 38. A knowledge-based algorithm for automatic detection of cephalometric landmarks on CBCT images.
    Gupta A; Kharbanda OP; Sardana V; Balachandran R; Sardana HK
    Int J Comput Assist Radiol Surg; 2015 Nov; 10(11):1737-52. PubMed ID: 25847662
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Artificial Intelligence and Machine Learning for Automated Cephalometric Landmark Identification: A Meta-Analysis Previewed by a Systematic Review.
    Rauniyar S; Jena S; Sahoo N; Mohanty P; Dash BP
    Cureus; 2023 Jun; 15(6):e40934. PubMed ID: 37496553
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Assessment of landmark detection in cephalometric radiographs with different conditions of brightness and contrast using the an artificial intelligence software.
    Menezes LDS; Silva TP; Lima Dos Santos MA; Hughes MM; Mariano Souza SDR; Leite Ribeiro PM; Freitas PHL; Takeshita WM
    Dentomaxillofac Radiol; 2023 Nov; 52(8):20230065. PubMed ID: 37869886
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 15.