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 *

137 related articles for article (PubMed ID: 37622568)

  • 21. Enhancing Stability and Performance in Mobile Robot Path Planning with PMR-Dueling DQN Algorithm.
    Deguale DA; Yu L; Sinishaw ML; Li K
    Sensors (Basel); 2024 Feb; 24(5):. PubMed ID: 38475059
    [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. Lateral Cephalometric Landmark Annotation Using Histogram Oriented Gradients Extracted from Region of Interest Patches.
    Rashmi S; Srinath S; Patil K; Murthy PS; Deshmukh S
    J Maxillofac Oral Surg; 2023 Dec; 22(4):806-812. PubMed ID: 38105853
    [TBL] [Abstract][Full Text] [Related]  

  • 24. 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]  

  • 25. Automatic analysis of lateral cephalograms based on high-resolution net.
    Chang Q; Wang Z; Wang F; Dou J; Zhang Y; Bai Y
    Am J Orthod Dentofacial Orthop; 2023 Apr; 163(4):501-508.e4. PubMed ID: 36528536
    [TBL] [Abstract][Full Text] [Related]  

  • 26. 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]  

  • 27. 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]  

  • 28. 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]  

  • 29. Accuracy of automated 3D cephalometric landmarks by deep learning algorithms: systematic review and meta-analysis.
    Serafin M; Baldini B; Cabitza F; Carrafiello G; Baselli G; Del Fabbro M; Sforza C; Caprioglio A; Tartaglia GM
    Radiol Med; 2023 May; 128(5):544-555. PubMed ID: 37093337
    [TBL] [Abstract][Full Text] [Related]  

  • 30. 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]  

  • 31. Evaluation of deep learning and convolutional neural network algorithms accuracy for detecting and predicting anatomical landmarks on 2D lateral cephalometric images: A systematic review and
    Londono J; Ghasemi S; Hussain Shah A; Fahimipour A; Ghadimi N; Hashemi S; Khurshid Z; Dashti M
    Saudi Dent J; 2023 Jul; 35(5):487-497. PubMed ID: 37520606
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Accuracy of automated identification of lateral cephalometric landmarks using cascade convolutional neural networks on lateral cephalograms from nationwide multi-centres.
    Kim J; Kim I; Kim YJ; Kim M; Cho JH; Hong M; Kang KH; Lim SH; Kim SJ; Kim YH; Kim N; Sung SJ; Baek SH
    Orthod Craniofac Res; 2021 Dec; 24 Suppl 2():59-67. PubMed ID: 33973341
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Accuracy of 3D cephalometric measurements based on an automatic knowledge-based landmark detection algorithm.
    Gupta A; Kharbanda OP; Sardana V; Balachandran R; Sardana HK
    Int J Comput Assist Radiol Surg; 2016 Jul; 11(7):1297-309. PubMed ID: 26704370
    [TBL] [Abstract][Full Text] [Related]  

  • 34. Deep Anatomical Context Feature Learning for Cephalometric Landmark Detection.
    Oh K; Oh IS; Le VNT; Lee DW
    IEEE J Biomed Health Inform; 2021 Mar; 25(3):806-817. PubMed ID: 32750939
    [TBL] [Abstract][Full Text] [Related]  

  • 35. MonkeyKing: Adaptive Parameter Tuning on Big Data Platforms with Deep Reinforcement Learning.
    Du H; Han P; Xiang Q; Huang S
    Big Data; 2020 Aug; 8(4):270-290. PubMed ID: 32654536
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Simplified Deep Reinforcement Learning Approach for Channel Prediction in Power Domain NOMA System.
    Gaballa M; Abbod M
    Sensors (Basel); 2023 Nov; 23(21):. PubMed ID: 37960708
    [TBL] [Abstract][Full Text] [Related]  

  • 37. An evaluation of cellular neural networks for the automatic identification of cephalometric landmarks on digital images.
    Leonardi R; Giordano D; Maiorana F
    J Biomed Biotechnol; 2009; 2009():717102. PubMed ID: 19753320
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Cephalogram synthesis and landmark detection in dental cone-beam CT systems.
    Huang Y; Fan F; Syben C; Roser P; Mill L; Maier A
    Med Image Anal; 2021 May; 70():102028. PubMed ID: 33744833
    [TBL] [Abstract][Full Text] [Related]  

  • 39. Clinical applicability of automated cephalometric landmark identification: Part I-Patient-related identification errors.
    Tanikawa C; Lee C; Lim J; Oka A; Yamashiro T
    Orthod Craniofac Res; 2021 Dec; 24 Suppl 2():43-52. PubMed ID: 34021976
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Improved Double Deep Q-Network Algorithm Applied to Multi-Dimensional Environment Path Planning of Hexapod Robots.
    Chen L; Wang Q; Deng C; Xie B; Tuo X; Jiang G
    Sensors (Basel); 2024 Mar; 24(7):. PubMed ID: 38610271
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 7.