--- a +++ b/README.md @@ -0,0 +1,5 @@ +# Prediction-of-Risk-of-Sepsis-using-ML-models-on-big-data +Determine the development of sepsis in hospital-administered patients earlier than the clinical predictions. +Data has been collected from over 1 million ICU patients with up to 40 clinical variables from 3 separate hospitals. +Various machine learning model was tried like Logistic Regression, SVM, Naïve Bayes, Random Forest. +Random Forest performs the best with an accuracy of 87% and f1 score of 91%.