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Big data in digital healthcare: lessons learnt and recommendations for general practice

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dc.contributor.author Agrawal, Raag en_US
dc.contributor.author PRABAKARAN, SUDHAKARAN en_US
dc.date.accessioned 2020-03-20T11:22:22Z
dc.date.available 2020-03-20T11:22:22Z
dc.date.issued 2020-04 en_US
dc.identifier.citation Heredity , 124(4), 525–534. en_US
dc.identifier.issn 1365-2540 en_US
dc.identifier.uri http://dr.iiserpune.ac.in:8080/xmlui/handle/123456789/4500
dc.identifier.uri https://doi.org/10.1038/s41437-020-0303-2 en_US
dc.description.abstract Big Data will be an integral part of the next generation of technological developments—allowing us to gain new insights from the vast quantities of data being produced by modern life. There is significant potential for the application of Big Data to healthcare, but there are still some impediments to overcome, such as fragmentation, high costs, and questions around data ownership. Envisioning a future role for Big Data within the digital healthcare context means balancing the benefits of improving patient outcomes with the potential pitfalls of increasing physician burnout due to poor implementation leading to added complexity. Oncology, the field where Big Data collection and utilization got a heard start with programs like TCGA and the Cancer Moon Shot, provides an instructive example as we see different perspectives provided by the United States (US), the United Kingdom (UK) and other nations in the implementation of Big Data in patient care with regards to their centralization and regulatory approach to data. By drawing upon global approaches, we propose recommendations for guidelines and regulations of data use in healthcare centering on the creation of a unique global patient ID that can integrate data from a variety of healthcare providers. In addition, we expand upon the topic by discussing potential pitfalls to Big Data such as the lack of diversity in Big Data research, and the security and transparency risks posed by machine learning algorithms. en_US
dc.language.iso en en_US
dc.publisher Springer Nature en_US
dc.subject Biology en_US
dc.subject TOC-MAR-2020 en_US
dc.subject 2020 en_US
dc.subject 2020-MAR-WEEK3 en_US
dc.title Big data in digital healthcare: lessons learnt and recommendations for general practice en_US
dc.type Article en_US
dc.contributor.department Dept. of Biology en_US
dc.identifier.sourcetitle Heredity en_US
dc.publication.originofpublisher Foreign en_US


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