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23 Mendeley
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Article details
Title
Man versus Machine: Software Training for Surgeons—An Objective Evaluation of Human and Computer‐Based Training Tools for Cataract Surgical Performance
Published in
Journal of Ophthalmology, October 2016
DOI 10.1155/2016/3548039
Pubmed ID
Authors
Abstract

This study aimed to address two queries: firstly, the relationship between two cataract surgical feedback tools for training, one human and one software based, and, secondly, evaluating microscope control during phacoemulsification using the software. Videos of surgeons with varying experience were enrolled and independently scored with the validated PhacoTrack motion capture software and the Objective Structured Assessment of Cataract Surgical Skill (OSACCS) human scoring tool. Microscope centration and path length travelled were also evaluated with the PhacoTrack software. Twenty-two videos correlated PhacoTrack motion capture with OSACCS. The PhacoTrack path length, number of movements, and total procedure time were found to have high levels of Spearman's rank correlation of -0.6792619 (p = 0.001), -0.6652021 (p = 0.002), and -0.771529 (p = 0001), respectively, with OSACCS. Sixty-two videos evaluated microscope camera control. Novice surgeons had their camera off the pupil centre at a far greater mean distance (SD) of 6.9 (3.3) mm, compared with experts of 3.6 (1.6) mm (p ≪ 0.05). The expert surgeons maintained good microscope camera control and limited total pupil path length travelled 2512 (1031) mm compared with novices of 4049 (2709) mm (p ≪ 0.05). Good agreement between human and machine quantified measurements of surgical skill exists. Our results demonstrate that surrogate markers for camera control are predictors of surgical skills.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 5 22%
Other 3 13%
Student > Bachelor 3 13%
Researcher 2 9%
Student > Postgraduate 2 9%
Other 5 22%
Unknown 3 13%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 11 48%
Engineering 3 13%
Social Sciences 2 9%
Biochemistry, Genetics and Molecular Biology 1 4%
Linguistics 1 4%
Other 2 9%
Unknown 3 13%