An Intelligent Medical Decision Support System Using Various Machine Learning Algorithms
Information is stored in various domains like finance, banking, hospital, education, etc. Nowadays, data stored in medical databases are growing rapidly. Handling each voluminous database manually to predict risk factors affecting patients frequently is highly impossible. Hence, the main aim of this work is to design machine-based diagnostic approach using various techniques. Evolving new machine learning techniques are necessary to provide better health care and raise an early warning to patients affected by various diseases. These algorithms improve the efficiency of mining risk factors of chronic kidney diseases, but there are also have some shortcomings. To overcome these issues, improve an effectual clinical decision support system exhausting machine learning methods over a large volume of the dataset for making better decisions and predictions.