The surgical patient mortality rate prediction by machine learning algorithms

Abstract

Malnutrition is a common problem in critical illness patients which is observed in patients who is undergoing for surgery and hospital mortality rate. The study found that patients undergone surgery who have malnutrition problem result in high death risk. In this research, we aim to predict the mortality rate of undergone surgery patient by using Chiang Rai Nutrition Assessment information (CNA) with various data mining models; J48, ADTree and KNN. Results from this study will help doctor to plan for patient health preparation before undergo surgery such as consumption behavior of patient. Besides, the approach developed in this study should be of value for future studies into understanding the effect of malnutrition in patient surgery result.