The Contemporary Ethical and Privacy Issues of Smart Medical Fields

The Contemporary Ethical and Privacy Issues of Smart Medical Fields

Victor Chang, Yujie Shi, Yan Zhang
Copyright: © 2021 |Pages: 10
DOI: 10.4018/978-1-7998-8954-0.ch092
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Abstract

With the development of big data technology, such as data mining and data matching, many industries have started a revolution, including medical field. Big data not only strengthens the accuracy of medical diagnosis, but it also enhances the efficiency of the entire medical system and relevant medical staff. Additionally, with the rethinking of innovation, the application of wearable intelligent device, RFID technology and sensor technology play positive roles in promoting medical interaction between hospital system and wearer. Smart medical provides effective methods for individual health management and promotes the progress of medical information. However, there are also some inevitable ethical problems, e.g., the leakage of privacy information, which cannot be avoided to some extents. The authors recommend some suggestions to reduce the possibilities of ethical problems happened during the data flow process.
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2. Literature Review

As the “new oil” in the 21st century, big data has become a hot topic in all walks of life. People have realized that big data can offer great opportunities in various fields such as commerce, healthcare and government. However, there are different versions of big data definitions. Big data can be defined as “relative terms” (Minelli et al., 2013) to describe the rapid development of computer technology and the dramatic increase in data volume (Albrecht & Fangerau, 2015). In the dialectical way of thinking, the definition of big data has four main aspects: a) Some scholars focus on the attributes of data, including the size, speed and diversity of data in order to highlight the novelty of big data (Laney, 2001). b) Other scholars focus their attention on the entire process, focusing on the collection, management and use of data. That is, data found through data processing (Boyd & Crawford, 2011). c) Of course, some scholars have also focused their attention on big data, especially on exploring the limitations of big data. In particular, Boyd and Crawford (2011) consider big data to describe the ability of businesses or individuals to collect, organize and use large databases. d) On the basis of the first three points of perception, some scholars have focused their attention on the socio-economic, cultural and political conditions underlying the phenomenon of big data (Ekbia et al., 2015). IBM does not define in that particular way, but rather in terms of quantity, breed, speed, and accuracy (IBM, 2017).

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