Search alternatives:
mean decrease » a decrease (Expand Search)
ms decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
ng decrease » nn decrease (Expand Search), _ decrease (Expand Search), a decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
50 ms » 50 mg (Expand Search), 50 mm (Expand Search)
mean decrease » a decrease (Expand Search)
ms decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
ng decrease » nn decrease (Expand Search), _ decrease (Expand Search), a decrease (Expand Search)
we decrease » _ decrease (Expand Search), a decrease (Expand Search), nn decrease (Expand Search)
50 ms » 50 mg (Expand Search), 50 mm (Expand Search)
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Paeameter ranges and optimal values.
Published 2025“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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384
Improved random forest algorithm.
Published 2025“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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385
Datasets used in the study area.
Published 2025“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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386
Evaluation of the improved random forest model.
Published 2025“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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387
Comparison of model metrics.
Published 2025“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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388
Flowchart of population spatialization.
Published 2025“…Firstly, recursive feature elimination using cross validation (RFECV), maximum information coefficient (MIC), and mean decrease accuracy (MDA) methods were utilized to select population distribution feature factors. …”
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389
Annual treatment frequencies in all eyes.
Published 2025“…<p>The number of anti-VEGF treatments, STTA, MA-PC, PPV, and total treatments (mean ± SD) significantly decreased from 2.6 ± 1.6, 0.3 ± 0.8, 0.6 ± 0.8, 0.1 ± 0.3, and 3.7 ± 1.7 preoperatively to 0.8 ± 1.9, 0.0 ± 0.2, 0.3 ± 1.0, 0.0, and 1.2 ± 2.2; at year 2 to 0.7 ± 2.0, 0.1 ± 0.6, 0.0 ± 0.2, 0.0 ± 0.2, and 1.0 ± 2.1; and at year 3 to 0.9 ± 2.2, 0.0, 0.2 ± 1.0, 0.0 ± 0.2, and 1.1 ± 3.1 (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
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390
Annual number of outpatient visits in recurrence and non-recurrence groups.
Published 2025“…<p>In the recurrence group, mean outpatient visits (± standard deviation) decreased from 13.6 ± 3.0 to 11.9 ± 5.0, 8.1 ± 3.9, and 7.8 ± 3.2 at 1, 2, and 3 years postoperatively, respectively (Kruskal-Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
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391
Annual number of outpatient visits in all eyes.
Published 2025“…<p>Mean visit frequency (mean ± standard deviation) significantly decreased from 11.5 ± 4.3 preoperatively to 8.8 ± 4.1, 5.0 ± 3.4, and 4.4 ± 3.2 visits in the first, second, and third postoperative years, respectively (Kruskal–Wallis test, P < 0.001; Dunn’s test, **P < 0.01). …”
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392
Annual treatment frequencies in recurrence and non-recurrence groups.
Published 2025“…(<a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0332941#pone.0332941.g007" target="_blank">Fig 7</a>). Mean outpatient visits in the recurrence group decreased from 13.6 ± 3.0 to 11.9 ± 5.0, 8.1 ± 3.9, and 7.8 ± 3.2 at 1, 2, and 3 years postoperatively, respectively (Kruskal-Wallis test, p < 0.001). …”
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