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Table 2 Statistical metrics for experiment #1

From: Assessing artificial intelligence ability in predicting hospitalization duration for pleural empyema patients managed with uniportal video-assisted thoracoscopic surgery: a retrospective observational study

Metric

Value

MAE (days)

4.56

MRSE (days)

6.16

MAPE (%)

53.79%

RR

−0.09

EVS

−0.09

MedAE (days)

3.29

AP (%)

46.21%

  1. This table summarizes the performance of the Random Forest model in predicting LOS. Metrics include Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and R-squared (R2), indicating the model's accuracy and limitations
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BMC Surgery

ISSN: 1471-2482

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