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. 2022 Feb 15;12:2473. doi: 10.1038/s41598-022-06438-7

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© The Author(s) 2022

Open AccessThis 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 licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence 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 licence, visit http://creativecommons.org/licenses/by/4.0/.

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Calibration curves for the optimized random forest models using the (left) demographic and ocular (DO) and (right) systemic, demographic and ocular (SDO) datasets. The flexible curve with pointwise confidence intervals (gray area) was based on local regression (loess). The bottom of the graph shows histograms of the predicted risks for eyes with complete success (1) and failure (0) at 1 year.