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Pupil diameter changes reflect difficulty and diagnostic accuracy during medical image interpretation

Overview of attention for article published in BMC Medical Informatics and Decision Making, July 2016
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Title
Pupil diameter changes reflect difficulty and diagnostic accuracy during medical image interpretation
Published in
BMC Medical Informatics and Decision Making, July 2016
DOI 10.1186/s12911-016-0322-3
Pubmed ID
Authors

Tad T. Brunyé, Marianna D. Eddy, Ezgi Mercan, Kimberly H. Allison, Donald L. Weaver, Joann G. Elmore

Abstract

No automated methods exist to objectively monitor and evaluate the diagnostic process while physicians review computerized medical images. The present study tested whether using eye tracking to monitor tonic and phasic pupil dynamics may prove valuable in tracking interpretive difficulty and predicting diagnostic accuracy. Pathologists interpreted digitized breast biopsies varying in diagnosis and rated difficulty, while pupil diameter was monitored. Tonic diameter was recorded during the entire duration of interpretation, and phasic diameter was examined when the eyes fixated on a pre-determined diagnostic region during inspection. Tonic pupil diameter was higher with increasing rated difficulty levels of cases. Phasic diameter was interactively influenced by case difficulty and the eventual agreement with consensus diagnosis. More difficult cases produced increases in pupil diameter, but only when the pathologists' diagnoses were ultimately correct. All results were robust after adjusting for the potential impact of screen brightness on pupil diameter. Results contribute new understandings of the diagnostic process, theoretical positions regarding locus coeruleus-norepinephrine system function, and suggest novel approaches to monitoring, evaluating, and guiding medical image interpretation.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 15%
Researcher 6 15%
Student > Master 5 12%
Student > Bachelor 3 7%
Other 3 7%
Other 7 17%
Unknown 11 27%
Readers by discipline Count As %
Computer Science 6 15%
Medicine and Dentistry 5 12%
Psychology 4 10%
Engineering 4 10%
Nursing and Health Professions 2 5%
Other 5 12%
Unknown 15 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 06 July 2016.
All research outputs
#20,335,423
of 22,880,230 outputs
Outputs from BMC Medical Informatics and Decision Making
#1,810
of 1,994 outputs
Outputs of similar age
#308,398
of 355,070 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#37
of 39 outputs
Altmetric has tracked 22,880,230 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,994 research outputs from this source. They receive a mean Attention Score of 4.9. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 39 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.