Smart Diagnosis of Disease Using Machine Learning

The impact of the morbidity in the long term leads to chronic disease and high mortality rates. Majority of the people suffering realize the chronic nature at the end stage. Machine learning can be integrated with the physician to deliver better solutions in identifying the nature of disease at early stages. The patients are diagnosed with the help of machine learning techniques and algorithms. Machine learning algorithms like Naïve Bayesian network, decision tree, random forest and support vector machine are integrated with the patient data to diagnose the disease and give the result of the patient's condition as normal or abnormal. After the diagnosis, medications are suggested for the disease. The general methods used for diagnosis are not affordable by the major population and machine learning methods can overcome the above limits.