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Status: Bibliographieeintrag

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Verfasst von:Reyes-González, Juan Pablo [VerfasserIn]   i
 Díaz-Peregrino, Roberto [VerfasserIn]   i
 Soto-Ulloa, Victor [VerfasserIn]   i
 Galvan-Remigio, Isabel [VerfasserIn]   i
 Castillo, Paul [VerfasserIn]   i
 Ogando-Rivas, Elizabeth [VerfasserIn]   i
Titel:Big data in the healthcare system
Titelzusatz:a synergy with artificial intelligence and blockchain technology
Verf.angabe:Reyes-González Juan Pablo, Díaz-Peregrino Roberto, Soto-Ulloa Victor, Galvan-Remigio Isabel, Castillo Paul and Ogando-Rivas Elizabeth
Jahr:2022
Umfang:16 S.
Fussnoten:Gesehen am 22.04.2024
Titel Quelle:Enthalten in: Journal of integrative bioinformatics
Ort Quelle:Berlin : Walter de Gruyter GmbH, 2004
Jahr Quelle:2022
Band/Heft Quelle:19(2022), 1, Seite 1-16
ISSN Quelle:1613-4516
Abstract:In the last decades big data has facilitating and improving our daily duties in the medical research and clinical fields; the strategy to get to this point is understanding how to organize and analyze the data in order to accomplish the final goal that is improving healthcare system, in terms of cost and benefits, quality of life and outcome patient. The main objective of this review is to illustrate the state-of-art of big data in healthcare, its features and architecture. We also would like to demonstrate the different application and principal mechanisms of big data in the latest technologies known as blockchain and artificial intelligence, recognizing their benefits and limitations. Perhaps, medical education and digital anatomy are unexplored fields that might be profitable to investigate as we are proposing. The healthcare system can be revolutionized using these different technologies. Thus, we are explaining the basis of these systems focused to the medical arena in order to encourage medical doctors, nurses, biotechnologies and other healthcare professions to be involved and create a more efficient and efficacy system.
DOI:doi:10.1515/jib-2020-0035
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

kostenfrei: Volltext: https://doi.org/10.1515/jib-2020-0035
 kostenfrei: Volltext: https://www.degruyter.com/document/doi/10.1515/jib-2020-0035/html
 DOI: https://doi.org/10.1515/jib-2020-0035
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:artificial intelligence
 big data
 blockchain
 healthcare system
 machine learning
K10plus-PPN:1886489823
Verknüpfungen:→ Zeitschrift

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