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Table 1.

Description of continuous features.

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Table 2.

Description of categorical features.

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Table 2 Expand

Fig 1.

Steps of Cobb angle measurement from frontal radiographs.

a. Plain frontal X-ray b. Four LMPs were selected per vertebra c. Polygon fit through each vertebra vertices (LMPs) d. Best fit ellipse through each polygon to calculate the orientation of each vertebra as the angle between the major axis of the ellipse and the horizontal e. A cubic spline was fit through the centroids of the vertebrae, the most tilted vertebrae above and below the apical level were identified, and the Cobb angle was calculated between these vertebrae.

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Fig 2.

Exemplar flexibility measurement.

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Table 3.

Indices of input features to RF model.

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Fig 3.

Flowchart of the curve progression model deployment.

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Table 4.

Output from SBFS ranked in descending order.

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Fig 4.

a. Rank of feature importance of most predictive features b. Frequency of prediction error of the testing dataset.

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Table 5.

Hyperparameters grid values and the selected values for optimized models.

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Table 6.

Performance of the ML models in terms of Mean Absolute Error (MAE).

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Table 7.

Rank and weights of most important features to predict curve progression.

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