Literature DB >> 27956140

Tired in the Reading Room: The Influence of Fatigue in Radiology.

Stephen Waite1, Srinivas Kolla2, Jean Jeudy3, Alan Legasto4, Stephen L Macknik5, Susana Martinez-Conde5, Elizabeth A Krupinski6, Deborah L Reede2.   

Abstract

Commonly conflated with sleepiness, fatigue is a distinct multidimensional condition with physical and mental effects. Fatigue in health care providers and any secondary effects on patient care are an important societal concern. As medical image interpretation is highly dependent on visual input, visual fatigue is of particular interest to radiologists. Humans analyze their surroundings with rapid eye movements called saccades, and fatigue decreases saccadic velocity. Oculomotor parameters may, therefore, be an objective and reproducible metric of fatigue and eye movement analysis can provide valuable insight into the etiology of fatigue-related error.
Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Fatigue; error; eye tracking; fixations; saccades

Mesh:

Year:  2016        PMID: 27956140     DOI: 10.1016/j.jacr.2016.10.009

Source DB:  PubMed          Journal:  J Am Coll Radiol        ISSN: 1546-1440            Impact factor:   5.532


  20 in total

1.  Increasing display luminance as a means to enhance interpretation accuracy and efficiency when reducing full-field digital mammography dose.

Authors:  Elizabeth A Krupinski
Journal:  J Med Imaging (Bellingham)       Date:  2018-07-27

2.  The Impact of Fatigue on Satisfaction of Search in Chest Radiography.

Authors:  Elizabeth A Krupinski; Kevin S Berbaum; Kevin M Schartz; Robert T Caldwell; Mark T Madsen
Journal:  Acad Radiol       Date:  2017-05-23       Impact factor: 3.173

3.  Review of learning opportunity rates: correlation with radiologist assignment, patient type and exam priority.

Authors:  Marla B K Sammer; Marcus D Sammer; Lane F Donnelly
Journal:  Pediatr Radiol       Date:  2019-07-17

Review 4.  Mandating Limits on Workload, Duty, and Speed in Radiology.

Authors:  Robert Alexander; Stephen Waite; Michael A Bruno; Elizabeth A Krupinski; Leonard Berlin; Stephen Macknik; Susana Martinez-Conde
Journal:  Radiology       Date:  2022-06-14       Impact factor: 29.146

5.  Advancing Research on Medical Image Perception by Strengthening Multidisciplinary Collaboration.

Authors:  Melissa Treviño; George Birdsong; Ann Carrigan; Peter Choyke; Trafton Drew; Miguel Eckstein; Anna Fernandez; Brandon D Gallas; Maryellen Giger; Stephen M Hewitt; Todd S Horowitz; Yuhong V Jiang; Bonnie Kudrick; Susana Martinez-Conde; Stephen Mitroff; Linda Nebeling; Joseph Saltz; Frank Samuelson; Steven E Seltzer; Behrouz Shabestari; Lalitha Shankar; Eliot Siegel; Mike Tilkin; Jennifer S Trueblood; Alison L Van Dyke; Aradhana M Venkatesan; David Whitney; Jeremy M Wolfe
Journal:  JNCI Cancer Spectr       Date:  2022-01-05

6.  Machine learning: a useful radiological adjunct in determination of a newly diagnosed glioma's grade and IDH status.

Authors:  Céline De Looze; Alan Beausang; Jane Cryan; Teresa Loftus; Patrick G Buckley; Michael Farrell; Seamus Looby; Richard Reilly; Francesca Brett; Hugh Kearney
Journal:  J Neurooncol       Date:  2018-05-16       Impact factor: 4.130

7.  Effect of fatigue on reading computed tomography examination of the multiply injured patient.

Authors:  Elizabeth A Krupinski; Kevin M Schartz; Mark S Van Tassell; Mark T Madsen; Robert T Caldwell; Kevin S Berbaum
Journal:  J Med Imaging (Bellingham)       Date:  2017-09-29

8.  Microsaccades in Applied Environments: Real-World Applications of Fixational Eye Movement Measurements.

Authors:  Robert G Alexander; Stephen L Macknik; Susana Martinez-Conde
Journal:  J Eye Mov Res       Date:  2020-05-15       Impact factor: 0.957

Review 9.  Challenges and optimization strategies in medical imaging service delivery during COVID-19.

Authors:  Yi Xiang Tay; Suchart Kothan; Sundaran Kada; Sihui Cai; Christopher Wai Keung Lai
Journal:  World J Radiol       Date:  2021-05-28

10.  Automated Detection of Pancreatic Cystic Lesions on CT Using Deep Learning.

Authors:  Lorraine Abel; Jakob Wasserthal; Thomas Weikert; Alexander W Sauter; Ivan Nesic; Marko Obradovic; Shan Yang; Sebastian Manneck; Carl Glessgen; Johanna M Ospel; Bram Stieltjes; Daniel T Boll; Björn Friebe
Journal:  Diagnostics (Basel)       Date:  2021-05-19
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