Machine Learning-Based Cardiovascular Disease Prediction

In contemporary times, cardiovascular diseases have emerged as a significant and critical cause of mortality for individuals. Therefore, it would be a boon for human existence that there exists a technology with high accuracy capable of detecting these diseases at an earlier phase but it has emerged as a challenge for data processing techniques. It has been surveyed that machine learning algorithms are capable of analysing, predicting and generating judgements. Due to advancements in IoT a variety of sensors had been developed that had contributed towards the development of better ML methods. In few articles it is observed that cardiovascular diseases are anticipated by examining the symptoms. Therefore, using machine learning techniques, a new and better solution in this domain is proposed that can predict cardiovascular diseases with better accuracy. The proposed article examines the probability of a cardiovascular disease in humans and classifies patient risk levels using various data mining techniques. This article brings out the analysis of various machine learning-based algorithms that are implemented to predict cardiovascular diseases.