A clinical decision-making mechanism for context-aware and patient-specific remote monitoring systems using the correlations of multiple vital signs

Highlights • We developed a clinical decision support system for vital sign predictions. • We used patient-specific vital sing correlations for detecting future value. • We utilized multi-label classification algorithms for classifier design. • Our developed tool can help doctors in diagnostic decision making. • Our developed model can support many patients simultaneously.