A Large-Scale Information Analysis Approach for Mammary Carcinoma Identification
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Today, the advancement of IT revolution, social and human endeavors have collectively created a torrent of data in the form of big data. This big data phenomenon will only get intensified and diversified in the years to come. Big data is becoming popular buzzword and apparent in many applications, such as healthcare, retail industry, business intelligence, social networks, social media and meteorology. As Big data is very large and complex, so one has to refine it to get meaningful information. The aim of this chapter is to provide description about big data, big data analytics, breast cancer ...
Today, the advancement of IT revolution, social and human endeavors have collectively created a torrent of data in the form of big data. This big data phenomenon will only get intensified and diversified in the years to come. Big data is becoming popular buzzword and apparent in many applications, such as healthcare, retail industry, business intelligence, social networks, social media and meteorology. As Big data is very large and complex, so one has to refine it to get meaningful information. The aim of this chapter is to provide description about big data, big data analytics, breast cancer and big data analytics for breast cancer. This chapter also covers big data in healthcare and various classification approaches for detection of breast cancer. Big Data Every day, data is generated by a range of different applications, devices and geographical research activities for the purposes of weather forecasting, weather prediction, disaster evaluation, crime detection and the health industry, to name a few [1]. In current scenario, big data is associated with core technologies and various enterprises including Google, Facebook, and IBM, which extract valuable information from the huge volumes of data collected [2]. An era of open information in healthcare is now under way. Big data is being generated rapidly in every field including healthcare, with respect to patient care, compliance and various regulatory requirements. As the global population continues to increase along with the human lifespan, treatment delivery models are evolving quickly, and some of the decisions underlying these fast changes must be based on data [3].
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