The healthcare industry generates huge data that cannot be handled manually. Using data mining methods, valuable information is extracted from this data to create a relationship between attributes. Machine learning algorithms and data mining techniques are used from data sets to predict the disease. Data mining techniques are used to study disease occurrence. One of the most frequently encountered problems in medical centres is that not all specialists are equally qualified and can give their own conclusion, which can cause the patient to die. Data mining techniques and machine learning algorithms play a dynamic role in the automatic diagnosis of diseases in health care centres to overcome such glitches prediction of diseases. The purpose of this survey paper is to analyse the prior health care research work and advanced disease analysis technologies. Support Vector Machine, Decision Tree, Naïve Bayes, K-Nearest Neighbour, and Artificial Neural Network are some machine algorithms used to predict the occurrence of diseases. Our study concludes that Support Vector Machine shows approximately 85% accuracy and has the potential to be considered as one of the disease prediction capable algorithms.

Data mining , Machine Learning, Support Vector Machine, Decision Tree, Naïve Bayes, K-Nearest Neighbor, and Artificial Neural Network

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