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Perceptual Learning of Appendicitis Diagnosis in Radiological Images
A sizeable body of work has demonstrated that participants have the capacity to show substantial increases in performance on perceptual tasks given appropriate practice. This has resulted in significant interest in the use of such perceptual learning techniques to positively impact performance in re...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
The Association for Research in Vision and Ophthalmology
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438669/ https://www.ncbi.nlm.nih.gov/pubmed/32790849 http://dx.doi.org/10.1167/jov.20.8.16 |
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author | Johnston, Ian Andrew Ji, Mohan Cochrane, Aaron Demko, Zachary Robbins, Jessica B. Stephenson, Jason W. Green, C. Shawn |
author_facet | Johnston, Ian Andrew Ji, Mohan Cochrane, Aaron Demko, Zachary Robbins, Jessica B. Stephenson, Jason W. Green, C. Shawn |
author_sort | Johnston, Ian Andrew |
collection | PubMed |
description | A sizeable body of work has demonstrated that participants have the capacity to show substantial increases in performance on perceptual tasks given appropriate practice. This has resulted in significant interest in the use of such perceptual learning techniques to positively impact performance in real-world domains where the extraction of perceptual information in the service of guiding decisions is at a premium. Radiological training is one clear example of such a domain. Here we examine a number of basic science questions related to the use of perceptual learning techniques in the context of a radiology-inspired task. On each trial of this task, participants were presented with a single axial slice from a CT image of the abdomen. They were then asked to indicate whether or not the image was consistent with appendicitis. We first demonstrate that, although the task differs in many ways from standard radiological practice, it nonetheless makes use of expert knowledge, as trained radiologists who underwent the task showed high (near ceiling) levels of performance. Then, in a series of four studies we show that (1) performance on this task does improve significantly over a reasonably short period of training (on the scale of a few hours); (2) the learning transfers to previously unseen images and to untrained image orientations; (3) purely correct/incorrect feedback produces weak learning compared to more informative feedback where the spatial position of the appendix is indicated in each image; and (4) there was little benefit seen from purposefully structuring the learning experience by starting with easier images and then moving on to more difficulty images (as compared to simply presenting all images in a random order). The implications for these various findings with respect to the use of perceptual learning techniques as part of radiological training are then discussed. |
format | Online Article Text |
id | pubmed-7438669 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | The Association for Research in Vision and Ophthalmology |
record_format | MEDLINE/PubMed |
spelling | pubmed-74386692020-08-28 Perceptual Learning of Appendicitis Diagnosis in Radiological Images Johnston, Ian Andrew Ji, Mohan Cochrane, Aaron Demko, Zachary Robbins, Jessica B. Stephenson, Jason W. Green, C. Shawn J Vis Article A sizeable body of work has demonstrated that participants have the capacity to show substantial increases in performance on perceptual tasks given appropriate practice. This has resulted in significant interest in the use of such perceptual learning techniques to positively impact performance in real-world domains where the extraction of perceptual information in the service of guiding decisions is at a premium. Radiological training is one clear example of such a domain. Here we examine a number of basic science questions related to the use of perceptual learning techniques in the context of a radiology-inspired task. On each trial of this task, participants were presented with a single axial slice from a CT image of the abdomen. They were then asked to indicate whether or not the image was consistent with appendicitis. We first demonstrate that, although the task differs in many ways from standard radiological practice, it nonetheless makes use of expert knowledge, as trained radiologists who underwent the task showed high (near ceiling) levels of performance. Then, in a series of four studies we show that (1) performance on this task does improve significantly over a reasonably short period of training (on the scale of a few hours); (2) the learning transfers to previously unseen images and to untrained image orientations; (3) purely correct/incorrect feedback produces weak learning compared to more informative feedback where the spatial position of the appendix is indicated in each image; and (4) there was little benefit seen from purposefully structuring the learning experience by starting with easier images and then moving on to more difficulty images (as compared to simply presenting all images in a random order). The implications for these various findings with respect to the use of perceptual learning techniques as part of radiological training are then discussed. The Association for Research in Vision and Ophthalmology 2020-08-13 /pmc/articles/PMC7438669/ /pubmed/32790849 http://dx.doi.org/10.1167/jov.20.8.16 Text en Copyright 2020 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. |
spellingShingle | Article Johnston, Ian Andrew Ji, Mohan Cochrane, Aaron Demko, Zachary Robbins, Jessica B. Stephenson, Jason W. Green, C. Shawn Perceptual Learning of Appendicitis Diagnosis in Radiological Images |
title | Perceptual Learning of Appendicitis Diagnosis in Radiological Images |
title_full | Perceptual Learning of Appendicitis Diagnosis in Radiological Images |
title_fullStr | Perceptual Learning of Appendicitis Diagnosis in Radiological Images |
title_full_unstemmed | Perceptual Learning of Appendicitis Diagnosis in Radiological Images |
title_short | Perceptual Learning of Appendicitis Diagnosis in Radiological Images |
title_sort | perceptual learning of appendicitis diagnosis in radiological images |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7438669/ https://www.ncbi.nlm.nih.gov/pubmed/32790849 http://dx.doi.org/10.1167/jov.20.8.16 |
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