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Prediction of fall events during admission using eXtreme gradient boosting: a comparative validation study

As the performance of current fall risk assessment tools is limited, clinicians face significant challenges in identifying patients at risk of falling. This study proposes an automatic fall risk prediction model based on eXtreme gradient boosting (XGB), using a data-driven approach to the standardiz...

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Bibliografske podrobnosti
izdano v:Sci Rep
Main Authors: Hsu, Yin-Chen, Weng, Hsu-Huei, Kuo, Chiu-Ya, Chu, Tsui-Ping, Tsai, Yuan-Hsiung
Format: Artigo
Jezik:Inglês
Izdano: Nature Publishing Group UK 2020
Teme:
Online dostop:https://ncbi.nlm.nih.gov/pmc/articles/PMC7544690/
https://ncbi.nlm.nih.gov/pubmed/33033326
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-020-73776-9
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