Heart Disease Identification Using Machine Learning Algorithm

After all advancements in technology and times, prediction and prevention of heart diseases is still a major issue in modern days. Heart diseases play a major role in high death rate in India. But with advancements of artificial technology and machine learning algorithms and programs several models are created to sort this problem in the health system. The following research paper is a source of a collective review of researches done recently in the field of predicting and preventing heart disease using AI and ML methods. This paper has meet various methods and models being used in predicting heart diseases using various parameters and criteria. It consists of data collection, methodology of making a model which gives out better accuracy, techniques to support and an evaluation of model. There are several methods for the prediction of heart diseases like risk factor identification, decision tree, logistic regression, random forest, gradient boosting machines(GBM), etc. Moreover, we have discussed modern trends, emerging techs and challenges or considerations to cover this problem in this field. It interprets and focuses light on different AI models, considerations and ethical aspects of recent research papers based on predicting heart diseases using AI/ML algorithms and models. In conclusion, the paper emerges light on the advancement and potential of AI/ML techniques to predict heart diseases and reduce early death rate and increase early treatments. However, further study and research is required to qualify more aspects.