Health Care Analysis Using Machine Learning

The objective of this study was to design and develop a discharge roster of a patient using machine learning techniques. The proposed method of discharge predictive model was then validated with the evaluation metrics used risk from ml tools. The study on a consisted  health Data set of actual data which has features of severity, department etc., We developed a machine learning model to predict a patient’s using the model types: Logistic Regression, Random Forests and Light Gradient Boosting with best params with different feature combinations and pre-processing procedures. The proposed model achieved the better accuracy when compared with the all existing systems. When compared with SVM and NN models, the proposed model achieved better accuracy by compared.

KEYWORDS: Machine learning, LGBM, Random Forests, detection.