Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning

Accuracy in predicting ED arrivals, achieved through the FE approach, is key for managing human and material resources, as well as reducing patient waiting times and lengths of stay.

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Institutions

Publication Details

Journal
BMC Medical Informatics and Decision Making
Published
2024-12-18
DOI
https://doi.org/10.1186/s12911-024-02788-6
Citations
21
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
14.51
Controls
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article

Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning

Bruno Matos Porto, Flávio S. Fogliatto
21 citations
BMC Medical Informatics and Decision Making
Emergency and Acute Care Studies
14.51
article

Enhanced forecasting of emergency department patient arrivals using feature engineering approach and machine learning

Bruno Matos Porto, Flávio S. Fogliatto
article en
21 citations

Abstract

Accuracy in predicting ED arrivals, achieved through the FE approach, is key for managing human and material resources, as well as reducing patient waiting times and lengths of stay.

BMC Medical Informatics and Decision MakingVol. 24(1)
Universidade Federal do Rio Grande do Sul (BR)
Openalex Percentile: Top 1%
Emergency and Acute Care Studies
14.51
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