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. 2024 Feb 28;46:100747. doi: 10.1016/j.ctro.2024.100747

Table 2.

ML model prediction performance for external (EXT) and internal (INT) lymphedema for the two patient cohorts.

EXT lymphedema (entire cohort) Mean
1 standard deviation
Accuracy F1-score AUC Accuracy F1-score AUC
Logit 67.2 71.7 77.1 3.5 3.8 12.3
SVM 64.5 68.4 77.6 2.8 5.8 13
XGB 77.7 85.1 78.2 2.9 2.7 12.7
RF 74.9 83.3 79.1 5.3 3.8 11.2



INT lymphedema (entire cohort)
Logit 69.9 59 74.5 8 17.4 9
SVM 63.3 55.8 70.7 7.4 18.1 9.2
XGB 76.3 66.9 79.5 6.7 13 7.8
RF 67.3 60.1 76 10 10.9 8.1



EXT lymphedema (oropharengeal cohort)
Logit 58.7 68.1 70.9 10.9 10 20.2
SVM 76.2 86 68.2 3.1 3 22.5
XGB 84.9 91.3 67.6 4.9 2.6 28.3
RF 78.4 87.6 74.3 6 3.5 22.4
INT lymphedema (oropharengeal cohort)
Logit 73.8 65.3 79.9 16.8 20.7 9.5
SVM 71.6 63.9 77.8 18.2 21.4 10.9
XGB 78.4 64.1 84.3 9.3 20 15.5
RF 80.7 70.4 83.7 12.3 20.4 15.3

Logit = Logistic regression, SVM = Support Vector Machine, XGB = Extreme Gradient Boosting,RF = Random Forest.