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  Dynamic patterns of expertise: The case of orthopedic medical diagnosis

Assaf, D., Amar, E., Marwan, N., Neuman, Y., Salai, M., Rath, E. (2016): Dynamic patterns of expertise: The case of orthopedic medical diagnosis. - PloS ONE, 11, 7, e0158820.
https://doi.org/10.1371/journal.pone.0158820

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Assaf, D.1, Author
Amar, E.1, Author
Marwan, Norbert2, Author              
Neuman, Y.1, Author
Salai, M.1, Author
Rath, E.1, Author
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1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: The aim of this study was to analyze dynamic patterns for scanning femoroacetabular impingement (FAI) radiographs in orthopedics, in order to better understand the nature of expertise in radiography. Seven orthopedics residents with at least two years of expertise and seven board-certified orthopedists participated in the study. The participants were asked to diagnose 15 anteroposterior (AP) pelvis radiographs of 15 surgical patients, diagnosed with FAI syndrome. Eye tracking data were recorded using the SMI desk-mounted tracker and were analyzed using advanced measures and methodologies, mainly recurrence quantification analysis. The expert orthopedists presented a less predictable pattern of scanning the radiographs although there was no difference between experts and non-experts in the deterministic nature of their scan path. In addition, the experts presented a higher percentage of correct areas of focus and more quickly made their first comparison between symmetric regions of the pelvis. We contribute to the understanding of experts’ process of diagnosis by showing that experts are qualitatively different from residents in their scanning patterns. The dynamic pattern of scanning that characterizes the experts was found to have a more complex and less predictable signature, meaning that experts’ scanning is simultaneously both structured (i.e. deterministic) and unpredictable.

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 Dates: 2016
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1371/journal.pone.0158820
PIKDOMAIN: Transdisciplinary Concepts & Methods - Research Domain IV
eDoc: 7505
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Health
Model / method: Nonlinear Data Analysis
Organisational keyword: RD4 - Complexity Science
Working Group: Development of advanced time series analysis techniques
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Title: PloS ONE
Source Genre: Journal, SCI, Scopus, p3, OA
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Pages: - Volume / Issue: 11 (7) Sequence Number: e0158820 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/r1311121