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It is of critical importance to pay attention to a multitude of events that impact the health, both physiologically and pathologically. Occurring at once and expressed in various ways (systemic) aspects of the body lead to interaction between different cardiovascular parameters (i.e. such as minute ventilation and blood pressure) which results in accurate clinical evaluation. As a result, understanding and predicting diseases necessitate an integrated data collection of both structured and unstructured methods that draw on the enormous spectrum of clinical and non-clinical data to create a more thorough picture of disease depiction. Big data analytics has recently made its entrance into the healthcare industry, medical researchers are excited about an entirely new aspect of this research known as incorporating the newer concepts. Researchers are conducting research on healthcare data pertaining to both the data itself and the taxonomy of useful analytics that can be done on it.

Figure 1.3 Areas of big data analytics in medicine.

Expanding on this one would include three areas of big data analytics in medicine which is discussed in this chapter. These three research areas do not comprehensively showcase the many ways big data analytics are applied in medicine; instead, they provide a collection of loosely defined use cases where big data analytics is being employed as shown in Figure 1.3.