Medical Diagnosis: Implementation of Different Machine Learning Based Approaches

Medical diagnosis is the process of identifying medical diseases through different symptoms and medical test reports of a patient. Diagnosing a medical disease is challenging due to the large number of decision parameters associated with it. The doctors have to examine each decision parameter to detect a medical disease. In this process, much time of doctors is wasted. Thus, there is the need for some intelligent approaches that can automate medical diagnosis tasks and take the decision quickly. In this paper, we detected breast cancer and diabetes diseases using 10 existing machine learning approaches. From the comparative analysis, we observed that amongst all 10 machine learning approaches, the integrated ANN and GA approach outperformed all other classification approaches.