Post-deployment performance of a deep learning algorithm for normal and abnormal chest X-ray classification: A study at visa screening centers in the United Arab Emirates

Post-deployment performance of a deep learning algorithm for normal and abnormal chest X-ray classification: A study at visa screening centers in the United Arab Emirates

Background: Chest radiographs (CXRs) are widely used to screen for infectious diseases like tuberculosis and COVID-19 among migrants. At such high-volume settings, manual CXR reporting is challenging and integrating artificial intelligence (AI) algorithms into the workflow help to rule out normal fi...

Full description

Saved in:
Bibliographic Details
Main Authors: Amina Abdelqadir Mohamed AlJasmi, Hatem Ghonim, Mohyi Eldin Fahmy, Aswathy Nair, Shamie Kumar, Dennis Robert, Afrah Abdikarim Mohamed, Hany Abdou, Anumeha Srivastava, Bhargava Reddy
Format: Article
Language:English
Published: Elsevier 2024-12-01
Series:European Journal of Radiology Open
Subjects:
Chest radiograph
Abnormality
Visa screening
Artificial intelligence
Workflow
Agreement
Online Access:http://www.sciencedirect.com/science/article/pii/S2352047724000613
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://www.sciencedirect.com/science/article/pii/S2352047724000613

Similar Items