Smart Heart Attack Forewarning Model Using MapReduce Programming Paradigm

The information and communication technology (ICT)-related exponential growth has increased the demand for big data analytics (BDA). BDA involves the handling of a gigantic data for storage and investigation. The evolving field of BDA owns many challenges in various fields including drug delivery, healthcare, surveillance, weather forecasting, etc. In comparison with other industries, the need for big data in healthcare experiences more attention in present days. Initially, the data collected from remote healthcare services vary based on value, variety, velocity, veracity, and volume since the collection occurs at different locations using various devices. In research and development, there is an urge for an algorithm in risk prediction of heart attack. One of the major diseases related to mortality is cardiovascular disease (CVD). Further, an approach is introduced, and this approach has improved performance in terms of accuracy of 99%. However, in future works, it is recommended to focus on various other nature-inspired algorithms for diseases such as thyroid, diabetes, and so on.