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Computational health informatics in the big data age: a survey
Fang R., Pouyanfar S., Yang Y., Chen S., Iyengar S. ACM Computing Surveys49 (1):1-36,2016.Type:Article
Date Reviewed: Sep 21 2016

Global information and communications technology (ICT) resources have been changing lives; fast networks and mobile devices offer “always-on” services, extending the possibilities of personal computers (PCs). Besides social networks and the Internet of Things (IoT), healthcare services--both independently and in relation with the former two--are among the fastest emerging areas, exploiting and challenging the development of ICT. This survey gives an overview on the anticipated and expected progress of healthcare during this decade; for each processing phase of health data, it presents an extensive list of methods and systems existing in 2014.

According to the forecasts quoted by the authors, the amount of healthcare data is growing exponentially; according to IDC, in 2020, it will be more than an order of magnitude (ten times) of the amount of 2014. Beyond size, new requirements should be fulfilled: handling of heterogeneous data types, executing distributed transactions, enabling global access but preserving security and confidentiality, improving and spreading global standards and interchanging data among proprietary systems, the online analysis of data, dedicated decision support systems both for medical practitioners and clinical remote expert teams, microbiology and genetic data in more personalized medicine, integrating personal diagnostic sensors, mobile patient-advisor services in e-health, and archiving requirements and reusability of longitudinal data.

These requirements cannot be fulfilled by traditional relational databases alone; the handling of big data stored in hybrid clouds expands the capabilities of those with working but still immature technologies.

At the start, these tools were completely independent of the traditional ones. They handle diverse kinds of new unstructured data types (including biometric data, texts about patient care, professional textbooks and articles, and so on) distributed to file servers of data centers worldwide, but do not support transactions and sophisticated queries. Most of the solutions introduced in the survey are based on these NoSQL systems. In some cases, the method and tool chosen for meeting the needs of a special medical area are rather ad hoc.

The authors mention that the product repertoire of both the new Internet giants (Amazon, Google, Facebook) and the traditional vendors (IBM, Oracle/Teradata/Sun/Siebel, Microsoft, Dell/EMC, SAP) converge: they support heterogeneous systems with interfaces to NoSQL, traditional SQL, and NewSQL tools and products in hybrid clouds. These technologies and major application areas--including healthcare, microbiology, and genetics--are introduced for instance in Chen et al. [1].

In my opinion, the main value of the survey is its introduction to a broad range of methods and developed tools applied in nontraditional healthcare and microbiology. I propose this overview for those ICT professionals who are developing applications in these fields.

Reviewer:  K. Balogh Review #: CR144783 (1612-0905)
1) Chen, M.; Mao, S.; Zhang, Y.; Leung, V. C. M. Big data: related technologies, challenges and future prospects. Springer, New York, NY, 2014. See CR Rev. No. 142961 (1502-0126).
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