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. 2019 Oct 18;9:14990. doi: 10.1038/s41598-019-50677-0

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© The Author(s) 2019

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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The location of the subfield(s) that significantly contributed to the vision-related quality of life for each task. Shown are the eight quadrant subfields of the binocular integrated visual field (IVF) of Humphrey Field Analyzer Swedish Interactive Threshold Algorithm standard (SITA) 10-2. The two square fields indicate the upper and lower hemifields of 24-2. Each * indicates a significantly contributing subfield, as determined using the Random Forest machine-learning algorithm (p < 0.05). The sand pattern square of the lower hemifield of 24-2 also significantly contributed (p < 0.05).