Analysis and Performance of Machine Learning Algorithms on Disease Diagnosis

Healthcare is one of the most significant and challenging fields since the history of mankind. It can be defined as the maintenance or improvement of health via the prevention, diagnosis, treatment, recovery, or cure of disease, injury, illness, and other physical or mental deteriorations and disablements in people. The best way to deliver healthcare would be by utilizing all the current resources and techniques used in all sectors, particularly the medical and technical fields. This project aims at embedding Machine learning in healthcare to give a more sophisticated, accurate and well-defined approach to medical prognosis. The first part of the project aims at collecting various data about the prognosis and diagnosis of diseases from across the globe. This data is then methodically saved, stored and cleaned. The second part of the project introduces this problem statement into various ML algorithms and uses an ensemble of these algorithms.