Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Table 1.

Statistics on the raw dataset.

More »

Table 1 Expand

Table 2.

Features used for training the machine learning models.

More »

Table 2 Expand

Table 3.

Composition of the Feature-saving and Record-saving datasets.

More »

Table 3 Expand

Fig 1.

Pearson Matrix describing the relation among input features and the transition to the SP phase within 180 days.

More »

Fig 1 Expand

More »

Expand

Table 4.

Results of Visit-Oriented models on Feature-saving and Record-saving datasets at different time points.

More »

Table 4 Expand

Table 5.

Results of History-Oriented setting on Feature-saving and Record-saving datasets at 180, 360 and 720 days.

More »

Table 5 Expand

Fig 2.

Threshold analysis.

The choice of confidence threshold has different effects on the indicated variables. Analysis was performed with Random Forest and LSTM for Record Preserving datasets.

More »

Fig 2 Expand