Research Article

Real-Time Remote Patient Monitoring and Alarming System for Noncommunicable Lifestyle Diseases

Table 6

Performance comparison of tested classifiers for patient risk identification system (Acc for accuracy, Pre for precision, and F1 for F1-score).

ClassifierAccPreRecallF1Mean absolute error (MAE)Root mean square error (RMSE)

Random forest837583770.1720.42
Logistic regression887084760.1630.404
Decision tree747474740.2570.507
K-nearest neighbor827382760.180.425
Support vector machine847084760.1630.404
XGBoost797379760.2090.457