Patient Survival Prediction with Machine Learning Algorithms
Articles > Article ยท 2020
Authors: Mustafa Berkant SELEK, Saadet Sena Egeli, Yalcin Isler
Journal of Intelligent Systems with Applications, International, 2020, pp 93-96
Summary
In this study, the intensive care unit patient survival is predicted by machine learning algorithms according to the examinations performed in the first 24 hours. The data of intensive care patients collected from approximately two hundred hospitals over a period of one year were used. Algorithms are run in Python environment. Machine learning models were compared with the Cross-Validation method, and the random forest algorithm is used. The model made the prediction with 92,53% accuracy rate.