In this project, in order to find the severity level of covid-19 patients, supervised machine learning algorithms were used. The covid data was taken from an American Hospital online. Using a python program and a few python libraries, the models are run to find a good accuracy, low MAPE value, and high F1 score. One main finding is that the Neural Network algorithm is the best algorithm among other supervised machine learning algorithms to predict the severity level of a patient such as not risky, moderate, or risky. When this model is preferred to be used, it predicts the severity level with 88% accuracy and a 0.11 MAPE value.
In this project, in order to find the severity level of covid-19 patients, supervised machine learning algorithms were used. The covid data was taken from an American Hospital online. Using a python program and a few python libraries, the models are run to find a good accuracy, low MAPE value, and high F1 score. One main finding is that the Neural Network algorithm is the best algorithm among other supervised machine learning algorithms to predict the severity level of a patient such as not risky, moderate, or risky. When this model is preferred to be used, it predicts the severity level with 88% accuracy and a 0.11 MAPE value.
The project report is below. PREDICTING THE SEVERITY LEVEL OF COVID-19 PATIENTS.pdf