An excellent mortality prediction model based on support vector machine (SVM)-a pilot study
Chien‐Lung Chan, Chia‐Li Chen, Hsien-Wei Ting · 2010
Intensive care is one of the most important components of the modern medical system. Healthcare professionals need to utilize intensive care resources effectively. Mortality prediction models help physicians decide which patients require intensive care the most and which do not. This pilot study retrospectively collected data on 695 patients admitted to intensive care units and constructed a novel mortality prediction model with support vector machine (SVM). The accuracy of new model is good. The precision rate is 0.899. The recall rate is 0.902. The F-Measure is 0.899. The ROC curve is 0.932. This new model can support the physician's in intensive care decision making.