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 *

155 related articles for article (PubMed ID: 36753006)

  • 1. Detection of aspiration from images of a videofluoroscopic swallowing study adopting deep learning.
    Iida Y; Näppi J; Kitano T; Hironaka T; Katsumata A; Yoshida H
    Oral Radiol; 2023 Jul; 39(3):553-562. PubMed ID: 36753006
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Deep Learning Analysis to Automatically Detect the Presence of Penetration or Aspiration in Videofluoroscopic Swallowing Study.
    Kim JK; Choo YJ; Choi GS; Shin H; Chang MC; Park D
    J Korean Med Sci; 2022 Feb; 37(6):e42. PubMed ID: 35166079
    [TBL] [Abstract][Full Text] [Related]  

  • 3. Automated pharyngeal phase detection and bolus localization in videofluoroscopic swallowing study: Killing two birds with one stone?
    Bandini A; Smaoui S; Steele CM
    Comput Methods Programs Biomed; 2022 Oct; 225():107058. PubMed ID: 35961072
    [TBL] [Abstract][Full Text] [Related]  

  • 4. The effect of time on the automated detection of the pharyngeal phase in videofluoroscopic swallowing studies.
    Bandini A; Steele CM
    Annu Int Conf IEEE Eng Med Biol Soc; 2021 Nov; 2021():3435-3438. PubMed ID: 34891978
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Automatic Pharyngeal Phase Recognition in Untrimmed Videofluoroscopic Swallowing Study Using Transfer Learning with Deep Convolutional Neural Networks.
    Lee KS; Lee E; Choi B; Pyun SB
    Diagnostics (Basel); 2021 Feb; 11(2):. PubMed ID: 33668528
    [TBL] [Abstract][Full Text] [Related]  

  • 6. Autonomous Swallow Segment Extraction Using Deep Learning in Neck-Sensor Vibratory Signals From Patients With Dysphagia.
    Khalifa Y; Donohue C; Coyle JL; Sejdic E
    IEEE J Biomed Health Inform; 2023 Feb; 27(2):956-967. PubMed ID: 36417738
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Automated Laryngeal Invasion Detector of Boluses in Videofluoroscopic Swallowing Study Videos Using Action Recognition-Based Networks.
    Nam K; Lee C; Lee T; Shin M; Kim BH; Park JW
    Diagnostics (Basel); 2024 Jul; 14(13):. PubMed ID: 39001334
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Concordance Between Aspiration Detected on Upper Gastrointestinal Series and Videofluoroscopic Swallow Study in Bottle-Fed Children.
    Flax-Goldenberg R; Kulkarni KS; Carson KA; Pinto JM; Martin-Harris B; Lefton-Greif MA
    Dysphagia; 2016 Aug; 31(4):505-10. PubMed ID: 27048206
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Influence of frame rate in detecting oropharyngeal aspiration in paediatric videofluoroscopic swallow studies - An observational study.
    Frakking TT; David M; Chang AB; Sarikwal A; Humphries S; Day S; Weir KA
    Eur J Radiol; 2024 Jan; 170():111275. PubMed ID: 38142573
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Accuracy of endoscopic and videofluoroscopic evaluations of swallowing for oropharyngeal dysphagia.
    Giraldo-Cadavid LF; Leal-Leaño LR; Leon-Basantes GA; Bastidas AR; Garcia R; Ovalle S; Abondano-Garavito JE
    Laryngoscope; 2017 Sep; 127(9):2002-2010. PubMed ID: 27859291
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Adding Endoscopist-Directed Flexible Endoscopic Evaluation of Swallowing to the Videofluoroscopic Swallowing Study Increased the Detection Rates of Penetration, Aspiration, and Pharyngeal Residue.
    Park WY; Lee TH; Ham NS; Park JW; Lee YG; Cho SJ; Lee JS; Hong SJ; Jeon SR; Kim HG; Cho JY; Kim JO; Cho JH; Lee JS
    Gut Liver; 2015 Sep; 9(5):623-8. PubMed ID: 25473074
    [TBL] [Abstract][Full Text] [Related]  

  • 12. Detection and diagnosis of dental caries using a deep learning-based convolutional neural network algorithm.
    Lee JH; Kim DH; Jeong SN; Choi SH
    J Dent; 2018 Oct; 77():106-111. PubMed ID: 30056118
    [TBL] [Abstract][Full Text] [Related]  

  • 13. A Deep Learning Approach for MRI in the Diagnosis of Labral Injuries of the Hip Joint.
    Ni M; Wen X; Chen W; Zhao Y; Yuan Y; Zeng P; Wang Q; Wang Y; Yuan H
    J Magn Reson Imaging; 2022 Aug; 56(2):625-634. PubMed ID: 35081273
    [TBL] [Abstract][Full Text] [Related]  

  • 14. Deep Learning Localizes and Identifies Polyps in Real Time With 96% Accuracy in Screening Colonoscopy.
    Urban G; Tripathi P; Alkayali T; Mittal M; Jalali F; Karnes W; Baldi P
    Gastroenterology; 2018 Oct; 155(4):1069-1078.e8. PubMed ID: 29928897
    [TBL] [Abstract][Full Text] [Related]  

  • 15. A deep learning framework for automatic detection of arbitrarily shaped fiducial markers in intrafraction fluoroscopic images.
    Mylonas A; Keall PJ; Booth JT; Shieh CC; Eade T; Poulsen PR; Nguyen DT
    Med Phys; 2019 May; 46(5):2286-2297. PubMed ID: 30929254
    [TBL] [Abstract][Full Text] [Related]  

  • 16. Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?
    Langerhuizen DWG; Bulstra AEJ; Janssen SJ; Ring D; Kerkhoffs GMMJ; Jaarsma RL; Doornberg JN
    Clin Orthop Relat Res; 2020 Nov; 478(11):2653-2659. PubMed ID: 32452927
    [TBL] [Abstract][Full Text] [Related]  

  • 17. Application of deep learning technology for temporal analysis of videofluoroscopic swallowing studies.
    Jeong SY; Kim JM; Park JE; Baek SJ; Yang SN
    Sci Rep; 2023 Oct; 13(1):17522. PubMed ID: 37845272
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Automatic diagnosis for cysts and tumors of both jaws on panoramic radiographs using a deep convolution neural network.
    Kwon O; Yong TH; Kang SR; Kim JE; Huh KH; Heo MS; Lee SS; Choi SC; Yi WJ
    Dentomaxillofac Radiol; 2020 Dec; 49(8):20200185. PubMed ID: 32574113
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Machine learning analysis to automatically measure response time of pharyngeal swallowing reflex in videofluoroscopic swallowing study.
    Lee JT; Park E; Hwang JM; Jung TD; Park D
    Sci Rep; 2020 Sep; 10(1):14735. PubMed ID: 32895465
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Comparison of Convolutional Neural Network Models for Determination of Vocal Fold Normality in Laryngoscopic Images.
    Cho WK; Choi SH
    J Voice; 2022 Sep; 36(5):590-598. PubMed ID: 32873430
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 8.