Patient Risk Classification based on Vital Signs using Machine Learning Algorithm

Infectious disease is always a serious issue in the world due to the impact of the spread of the disease and mortality. Now a days heart disease is also the most common disease. Heart disease, chronic disease and COVID19 reflected by changes in vital signs. The major vital signs are blood pressure, pulse rate and body temperature. The evolution in Machine Learning plays an important role to improve healthcare facilities and save human lives. The effective diagnosis of heart disease in a shorter time is very important to save human lives. At the same time COVD-19 is also affecting many people worldwide. Machine learning techniques are used for diagnosis of disease. It uses datasets of earlier patient reports. This paper discusses machine algorithms to diagnose and differentiate infectious diseases, chronic disease, and heart disease. As a result, patients facing high risk can be shifted to the ICU and other patients to normal wards. These algorithms are effective in disease screening.