Literature DB >> 26063521

[Big data in medicine and healthcare].

Stefan Rüping1.   

Abstract

Healthcare is one of the business fields with the highest Big Data potential. According to the prevailing definition, Big Data refers to the fact that data today is often too large and heterogeneous and changes too quickly to be stored, processed, and transformed into value by previous technologies. The technological trends drive Big Data: business processes are more and more executed electronically, consumers produce more and more data themselves - e.g. in social networks - and finally ever increasing digitalization. Currently, several new trends towards new data sources and innovative data analysis appear in medicine and healthcare. From the research perspective, omics-research is one clear Big Data topic. In practice, the electronic health records, free open data and the "quantified self" offer new perspectives for data analytics. Regarding analytics, significant advances have been made in the information extraction from text data, which unlocks a lot of data from clinical documentation for analytics purposes. At the same time, medicine and healthcare is lagging behind in the adoption of Big Data approaches. This can be traced to particular problems regarding data complexity and organizational, legal, and ethical challenges. The growing uptake of Big Data in general and first best-practice examples in medicine and healthcare in particular, indicate that innovative solutions will be coming. This paper gives an overview of the potentials of Big Data in medicine and healthcare.

Mesh:

Year:  2015        PMID: 26063521     DOI: 10.1007/s00103-015-2181-y

Source DB:  PubMed          Journal:  Bundesgesundheitsblatt Gesundheitsforschung Gesundheitsschutz        ISSN: 1436-9990            Impact factor:   1.513


  5 in total

Review 1.  Activity Theory as a Theoretical Framework for Health Self-Quantification: A Systematic Review of Empirical Studies.

Authors:  Manal Almalki; Kathleen Gray; Fernando Martin-Sanchez
Journal:  J Med Internet Res       Date:  2016-05-27       Impact factor: 5.428

2.  Interpretable Clinical Decision Support System for Audiology Based on Predicted Common Audiological Functional Parameters (CAFPAs).

Authors:  Mareike Buhl
Journal:  Diagnostics (Basel)       Date:  2022-02-11

3.  Ethical Implications of e-Health Applications in Early Preventive Healthcare.

Authors:  Mandy Stake; Bert Heinrichs
Journal:  Front Genet       Date:  2022-07-08       Impact factor: 4.772

4.  Construction of a Legal System of Corporate Social Responsibility Based on Big Data Analysis Technology.

Authors:  Jiuzheng Pei
Journal:  J Environ Public Health       Date:  2022-10-07

5.  An African Relational Approach to Healthcare and Big Data Challenges.

Authors:  Cornelius Ewuoso
Journal:  Sci Eng Ethics       Date:  2021-05-28       Impact factor: 3.525

  5 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.