Artificial Intelligence and Cybersecurity in Preventing Sentinel Events

dc.contributor.authorTriplett, William J.
dc.date.accessioned2025-01-31T18:24:10Z
dc.date.available2025-01-31T18:24:10Z
dc.date.issued2024-12-31
dc.description.abstractThe study mainly focused on the impact of artificial intelligence (AI) in addressing sentinel occurrences in healthcare, particularly the unanticipated events that cause intensive patient harm. Through initiatives such as leveraging predictive analytics, machine learning algorithms, and processing of natural language, AI could help promote safety and prevent risks. This article evaluates the uses of AI, drawbacks, and the ethical implications while developing an understanding of how this innovation would boost patient care and cultural safety. Moreover, the paper examines the security issues related to AI-based healthcare to highlight the advantages of enforcing critical information safeguards while enhancing organizational dependability.
dc.description.urihttps://journal.gmpionline.com/index.php/citj/article/view/555
dc.format.extent6 pages
dc.genrejournal articles
dc.identifierdoi:10.13016/m2r3jt-tkt2
dc.identifier.citationTriplett, William J. "Artificial Intelligence and Cybersecurity in Preventing Sentinel Events". Cybersecurity and Innovative Technology Journal 2, no. 2 (December 31, 2024): 98�3. https://doi.org/10.53889/citj.v2i2.555.
dc.identifier.urihttps://doi.org/10.53889/citj.v2i2.555
dc.identifier.urihttp://hdl.handle.net/11603/37560
dc.language.isoen_US
dc.publisherGMPI
dc.relation.isAvailableAtThe University of Maryland, Baltimore County (UMBC)
dc.relation.ispartofUMBC Faculty Collection
dc.relation.ispartofUMBC Health Information Technology
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectSystems
dc.subjectHealthcare
dc.subjectArtificial intelligence
dc.subjectCybersecurity.
dc.subjectSentinel events
dc.titleArtificial Intelligence and Cybersecurity in Preventing Sentinel Events
dc.typeText

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