Literature DB >> 26844988

Informatics in neurocritical care: new ideas for Big Data.

Marine Flechet1, Fabian Güiza Grandas, Geert Meyfroidt.   

Abstract

PURPOSE OF REVIEW: Big data is the new hype in business and healthcare. Data storage and processing has become cheap, fast, and easy. Business analysts and scientists are trying to design methods to mine these data for hidden knowledge. Neurocritical care is a field that typically produces large amounts of patient-related data, and these data are increasingly being digitized and stored. This review will try to look beyond the hype, and focus on possible applications in neurointensive care amenable to Big Data research that can potentially improve patient care. RECENT
FINDINGS: The first challenge in Big Data research will be the development of large, multicenter, and high-quality databases. These databases could be used to further investigate recent findings from mathematical models, developed in smaller datasets. Randomized clinical trials and Big Data research are complementary. Big Data research might be used to identify subgroups of patients that could benefit most from a certain intervention, or can be an alternative in areas where randomized clinical trials are not possible.
SUMMARY: The processing and the analysis of the large amount of patient-related information stored in clinical databases is beyond normal human cognitive ability. Big Data research applications have the potential to discover new medical knowledge, and improve care in the neurointensive care unit.

Entities:  

Mesh:

Year:  2016        PMID: 26844988     DOI: 10.1097/MCC.0000000000000287

Source DB:  PubMed          Journal:  Curr Opin Crit Care        ISSN: 1070-5295            Impact factor:   3.687


  6 in total

1.  What's new in ICU in 2050: big data and machine learning.

Authors:  Sébastien Bailly; Geert Meyfroidt; Jean-François Timsit
Journal:  Intensive Care Med       Date:  2017-12-26       Impact factor: 17.440

Review 2.  Neurocritical Care: Bench to Bedside (Eds. Claude Hemphill, Michael James) Integrating and Using Big Data in Neurocritical Care.

Authors:  Brandon Foreman
Journal:  Neurotherapeutics       Date:  2020-04       Impact factor: 7.620

3.  Current Status and Recommendations in Multimodal Neuromonitoring.

Authors:  Radhika S Ruhatiya; Sachin A Adukia; Ramya B Manjunath; Harish M Maheshwarappa
Journal:  Indian J Crit Care Med       Date:  2020-05

4.  Clinical prediction models for acute kidney injury.

Authors:  Chao-Yuan Huang; Fabian Güiza Grandas; Marine Flechet; Geert Meyfroidt
Journal:  Rev Bras Ter Intensiva       Date:  2020-05-08

5.  Association of transcranial Doppler blood flow velocity slow waves with delayed cerebral ischemia in patients suffering from subarachnoid hemorrhage: a retrospective study.

Authors:  Vasilios E Papaioannou; Karol P Budohoski; Michal M Placek; Zofia Czosnyka; Peter Smielewski; Marek Czosnyka
Journal:  Intensive Care Med Exp       Date:  2021-03-26

Review 6.  Big Data in traumatic brain injury; promise and challenges.

Authors:  Denes V Agoston; Dianne Langford
Journal:  Concussion       Date:  2017-07-10
  6 in total

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