Survey of Big data Analytics in Medical Imaging

Big Data is promising for business application and is rapidly increasing as a segment of the IT industry. It has generated significant interest in various fields, including the manufacture of healthcare machines, banking transactions, social media, and satellite imaging [3]. The rapidly expanding field of big data analytics has started to play a pivotal role in the evolution of healthcare practices and research. It has provided tools to accumulate, manage, analyze, and assimilate large volumes of disparate, structured, and unstructured data produced by current healthcare systems. Big data in medical field also refers to the patient care data such as physician notes, Lab reports, X-Ray reports, case history, diet regime, list of doctors and nurses in a particular hospital, national health register data, medicine and surgical instruments expiry date identification based on RFID data. Healthcare organizations are depending on big data technology to capture all of this information about a patient to get a more complete view for insight into care coordination and outcomes-based reimbursement models, health management, and patient engagement. To improve the quality of healthcare by minimizing the costs, it's necessary that large volume of data generated should be analyzed effectively to answer new challenges. Similarly government also generates petabytes of data every day. It requires a technology that helps to perform a real time analysis on the enormous data set. Big data analytics helps in discovering valuable decisions by understanding the data patterns and the relationship between them with the help of machine learning algorithms [1].

This study presents: (a) a comprehensive survey of Big Data characteristics; (b) Need for Big Data Analytics in Healthcare; (c) the life cycle with Big Data aspects; and (d) discussion on areas of big data analytics in medicine (e) Conclusion and future works.