Artificial Intelligence and Cybersecurity in Preventing Sentinel Events
dc.contributor.author | Triplett, William J. | |
dc.date.accessioned | 2025-01-31T18:24:10Z | |
dc.date.available | 2025-01-31T18:24:10Z | |
dc.date.issued | 2024-12-31 | |
dc.description.abstract | The 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.uri | https://journal.gmpionline.com/index.php/citj/article/view/555 | |
dc.format.extent | 6 pages | |
dc.genre | journal articles | |
dc.identifier | doi:10.13016/m2r3jt-tkt2 | |
dc.identifier.citation | Triplett, 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.uri | https://doi.org/10.53889/citj.v2i2.555 | |
dc.identifier.uri | http://hdl.handle.net/11603/37560 | |
dc.language.iso | en_US | |
dc.publisher | GMPI | |
dc.relation.isAvailableAt | The University of Maryland, Baltimore County (UMBC) | |
dc.relation.ispartof | UMBC Faculty Collection | |
dc.relation.ispartof | UMBC Health Information Technology | |
dc.rights | Attribution 4.0 International | |
dc.rights.uri | https://creativecommons.org/licenses/by/4.0/ | |
dc.subject | Systems | |
dc.subject | Healthcare | |
dc.subject | Artificial intelligence | |
dc.subject | Cybersecurity. | |
dc.subject | Sentinel events | |
dc.title | Artificial Intelligence and Cybersecurity in Preventing Sentinel Events | |
dc.type | Text |
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