Using machine learning to identify top predictors for nurses’ willingness to report medication errors

Renjie Hu*, Amany Farag, Kaj-Mikael Björk, Amaury Lendasse

*Motsvarande författare för detta arbete

Forskningsoutput: TidskriftsbidragArtikelPeer review

Sammanfattning

This paper presents a novel methodology to analyze nurses’ willingness to report medication errors. Parallel Extreme Learning Machines were applied to identify the top interpersonal and organizational predictors and Self-Organizing Maps to create comprehensive visualization. The results of the data analysis were targeted to improve the likelihood of nurses reporting of medication errors. ELMs are accurate by extremely fast prediction models. Self-Organizing Maps enable us to perform non-linear dimensionality reduction to get an accurate visualization of the selected variables. Combining both techniques reduces the curse of dimensionality and improves the interpretability of the visualization.
OriginalspråkEngelska
Artikelnummer100049
Referentgranskad vetenskaplig tidskriftArray
Volym8
Sidor (från-till)100049
Antal sidor11
ISSN2590-0056
DOI
StatusPublicerad - 09.11.2020
MoE-publikationstypA1 Originalartikel i en vetenskaplig tidskrift

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