Clinical trial NCT03849040 - References

Lung Diseases — The Use of Artificial Intelligence to Predict Cancerous Lymph Nodes for Lung Cancer Staging During Ultrasound Imaging

Citation(s)

•   American College of Chest Physicians; Health and Science Policy Committee
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•   El-Sherief AH, Lau CT, Wu CC, Drake RL, Abbott GF, Rice TW
  International association for the study of lung cancer (IASLC) lymph node map: radiologic review with CT illustration. Radiographics. 2014 Oct;34(6):1680-91. doi: 10.1148/rg.346130097. Review.
•   Hanna WC, Yasufuku K
  Bronchoscopic staging of lung cancer. Ther Adv Respir Dis. 2013 Apr;7(2):111-8. doi: 10.1177/1753465812468041. Epub 2012 Dec 20. Review.
•   Hylton DA, Turner J, Shargall Y, Finley C, Agzarian J, Yasufuku K, Fahim C, Hanna WC
  Ultrasonographic characteristics of lymph nodes as predictors of malignancy during endobronchial ultrasound (EBUS): A systematic review. Lung Cancer. 2018 Dec;126:97-105. doi: 10.1016/j.lungcan.2018.10.020. Epub 2018 Oct 30.
•   Topol EJ
  High-performance medicine: the convergence of human and artificial intelligence. Nat Med. 2019 Jan;25(1):44-56. doi: 10.1038/s41591-018-0300-7. Epub 2019 Jan 7. Review.

Development and Validation of a Computer-aided Algorithm Using Artificial Intelligence and Deep Neural Networks for the Segmentation of Ultrasonographic Features of Lymph Nodes During Endobronchial Ultrasound

Details for clinical trial NCT03849040