Real-time machine learning for big data approach to early identification of heart disease

Abstract: The leading cause of death worldwide over the past few decades has been heart disease. Thus, regular monitoring and early detection of cardiac disease can lower the death rate. An vast amount of data has been continuously being generated by the exponential increase of data from various sources, including streaming systems, wearable sensor devices used in Internet of Things health monitoring, and others. A breakthrough in technology, streaming big data analytics and machine learning, has the potential to revolutionise the healthcare industry, particularly in the area of early heart disease detection. This technology might be more affordable and more potent. This research suggests a real-time cardiac disease prediction system built on Apache Spark to address this problem.

Keywords: big data, spark, distributed machine learning, heart disease, real-time