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AI for Timely Detection of Improper Tracheal Tube Placement: Where AI Can Readily Save Lives

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Manage episode 383810394 series 2590544
Content provided by American Roentgen Ray Society. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American Roentgen Ray Society or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29769

In this podcast, Bahram Mohajer, MD, MPH introduces a study on AI's role in assessing endotracheal tube positions on chest radiographs. The study demonstrates high sensitivity and specificity in identifying tube presence and positioning, especially in critical cases. The AI system's potential to expedite detection and reduce delays in repositioning is highlighted. While the study's strengths include a large sample size and multi-institutional data, the author acknowledges limitations such as the retrospective design and lack of clinical outcome data. The podcast concludes by emphasizing the promising impact of AI on radiologists' efficiency and patient safety, with the need for further validation and integration into diverse healthcare settings.

  continue reading

99 episodes

Artwork
iconShare
 
Manage episode 383810394 series 2590544
Content provided by American Roentgen Ray Society. All podcast content including episodes, graphics, and podcast descriptions are uploaded and provided directly by American Roentgen Ray Society or their podcast platform partner. If you believe someone is using your copyrighted work without your permission, you can follow the process outlined here https://player.fm/legal.

Full article: https://www.ajronline.org/doi/10.2214/AJR.23.29769

In this podcast, Bahram Mohajer, MD, MPH introduces a study on AI's role in assessing endotracheal tube positions on chest radiographs. The study demonstrates high sensitivity and specificity in identifying tube presence and positioning, especially in critical cases. The AI system's potential to expedite detection and reduce delays in repositioning is highlighted. While the study's strengths include a large sample size and multi-institutional data, the author acknowledges limitations such as the retrospective design and lack of clinical outcome data. The podcast concludes by emphasizing the promising impact of AI on radiologists' efficiency and patient safety, with the need for further validation and integration into diverse healthcare settings.

  continue reading

99 episodes

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