Authors :
Ibrahim Ahmed El-Imam; Sunday Ikpe; Mohammed Sani Ibrahim
Volume/Issue :
Volume 9 - 2024, Issue 12 - December
Google Scholar :
https://tinyurl.com/bddwabpv
Scribd :
https://tinyurl.com/2wsxjja4
DOI :
https://doi.org/10.5281/zenodo.14513182
Abstract :
Hospital-acquired infections (HAIs) represent
a serious threat to patient safety and the standard of
healthcare, leading to increased morbidity, longer
hospital stays, and more healthcare costs. With an
emphasis on AI methods that recognize infection trends
and evaluate risk variables linked to HAIs, this study
reviews recent research on the use of AI in predicting and
preventing HAI outbreaks. The findings indicate that AI
models have a lot of potential for early outbreak
identification, with predicted accuracy outperforming
conventional statistical techniques. Prompt alerts and
actions including AI-driven technologies for real-time
monitoring and infection prediction are essential for
lowering HAI incidence rates. However, while AI presents
valuable opportunities, its effective application will
necessitate resolving operational, ethical, and technical
issues that may arise.
Keywords :
Patient Safety, Digital Health, Technology, Infection Prevention, Disease Control.
References :
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Hospital-acquired infections (HAIs) represent
a serious threat to patient safety and the standard of
healthcare, leading to increased morbidity, longer
hospital stays, and more healthcare costs. With an
emphasis on AI methods that recognize infection trends
and evaluate risk variables linked to HAIs, this study
reviews recent research on the use of AI in predicting and
preventing HAI outbreaks. The findings indicate that AI
models have a lot of potential for early outbreak
identification, with predicted accuracy outperforming
conventional statistical techniques. Prompt alerts and
actions including AI-driven technologies for real-time
monitoring and infection prediction are essential for
lowering HAI incidence rates. However, while AI presents
valuable opportunities, its effective application will
necessitate resolving operational, ethical, and technical
issues that may arise.
Keywords :
Patient Safety, Digital Health, Technology, Infection Prevention, Disease Control.