Open AccessPatient Survival Prediction with Machine Learning Algorithms
Author(s) -
Mustafa Berkant Selek,
Saadet Sena Egeli,
Yalçın İşler
Publication year - 2020
Publication title -
akıllı sistemler ve uygulamaları dergisi
Language(s) - English
Resource type - Journals
ISSN - 2667-6893
DOI - 10.54856/jiswa.202012126
Subject(s) - machine learning , python (programming language) , random forest , artificial intelligence , algorithm , computer science , intensive care unit , intensive care , medicine , intensive care medicine , operating system
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.