A Convolutional Neural Network for Real Time Classification, Identification, and Labelling of Vocal Cord and Tracheal Using Laryngoscopy and Bronchoscopy Video-Reference-Cited by-同舟云学术

A Convolutional Neural Network for Real Time Classification, Identification, and Labelling of Vocal Cord and Tracheal Using Laryngoscopy and Bronchoscopy Video

Published:2020-01-02 Issue:2 Volume:44 Page:
ISSN:0148-5598
Container-title:Journal of Medical Systems
language:en
Short-container-title:J Med Syst

Author:

Matava Clyde^ORCID,Pankiv Evelina,Raisbeck Sam,Caldeira Monica,Alam Fahad

Publisher

Springer Science and Business Media LLC

Subject

Health Information Management,Health Informatics,Information Systems,Medicine (miscellaneous)

Link

http://link.springer.com/content/pdf/10.1007/s10916-019-1481-4.pdf

Reference15 articles.

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2. Chen, Y.-L., and Wu, K.-H., Airway Management of Patients with Craniofacial Abnormalities: 10-year experience at a teaching Hospital in Taiwan. Journal of the Chinese Medical Association 72(9):468–470, 2009.

3. Weiss, M., and Engelhardt, T., Proposal for the management of the unexpected difficult pediatric airway. Pediatric Anesthesia 20(5):454–464, 2010.

4. Aziz, M. F., Dillman, D., Fu, R., and Brambrink, A. M., Comparative effectiveness of the C-MAC video laryngoscope versus direct laryngoscopy in the setting of the predicted difficult airway. Anesthesiology 116(3):629–636, 2012.

5. Niforopoulou, P., Pantazopoulos, I., Demestiha, T., Koudouna, E., and Xanthos, T., Video-laryngoscopes in the adult airway management: A topical review of the literature. Acta Anaesthesiologica Scandinavica 54:1050–1061, 2010. https://doi.org/10.1111/j.1399-6576.2010.02285.x.

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