Detection of lung cancer on the chest radiograph: a study on observer performance-Reference-Cited by-同舟云学术

Detection of lung cancer on the chest radiograph: a study on observer performance

Published:2001-08 Issue:2 Volume:39 Page:111-116
ISSN:0720-048X
Container-title:European Journal of Radiology
language:en
Short-container-title:European Journal of Radiology

Author:

Quekel Lorentz G.B.A,Kessels Alphons G.H,Goei Reginald,van Engelshoven Joseph M.A

Publisher

Elsevier BV

Subject

Radiology, Nuclear Medicine and imaging,General Medicine

Reference24 articles.

1. Disagreements in chest roentgen interpretation;Herman;Chest,1975

2. Pneumoconiosis: interreader variability in the classification of the type of small opacities in the chest roentgenogram;Amandus;Am. J. Radiol.,1974

3. Interobserver variability in the interpretation of chest roentgenograms of patients with possible pneumonia;Young;Arch. Intern. Med.,1994

4. Interobserver reliability of the chest radiograph in community-acquired pneumonia. PORT Investigators;Albaum;Chest,1996

5. An assessment of inter-observer agreement and accuracy when reporting plain radiographs;Tudor;Clin. Radiol.,1997

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