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Pediatric healthcare poses distinctive challenges due to children's vulnerability and specific medical requirements [1]. Errors in nursing within such contexts can result in grave consequences, underscoring the critical importance of preventing such occurrences [2]. On the other hand, machine learning offers promising avenues for addressing these challenges by automating decision-making processes, improving diagnostic precision, and issuing real-time alerts to avert potential errors [3]. The objective of this paper is to furnish an exhaustive examination of the application of machine learning in ameliorating nursing errors in pediatric care, elucidating the technologies utilized, their practical applications, and the attained outcomes thus far.
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Soltani et al. (2024) studied this question.
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