Author : Neha S. Ahire and Shivaji R. Lahane

Data analytics has initiated to play a crucial role within the evolution of health care research and development. it’s given tools to collect , oversee, investigate, and absorb huge volumes of unique, organized, and unstructured information produced by current healthcare systems. Big data processing has been newly practiced towards aiding the method of healthcare precaution suggestion and disease risk prediction. Medical data processing has great potential to explore the hidden models in data sets of the medical domain. These models are often used for make a clinical diagnosis these data should be collected during a standardized form. Of the medical profiles six attributes are extracted, like age, sex, vital sign and blood glucose etc. can predict the likelihood of a patient contracting heart condition . These attributes are introduced within the machine learning algorithms, classification of decision tree in heart condition prediction, applying the technique of knowledge mining to cardiopathies treatment; it can provide a reliable performance like that achieved within the diagnosis of heart condition . For these medical industries it could offer a far better diagnosis and treatment of the patient to be achieved good quality of services. the most advantages of this document are: Timely detection of heart condition and its diagnosis in time and supply treatment at a reasonable cost.

Keywords: Machine learning, heart disease prediction, feature selection, prediction Model, classification algorithms