Artificial intelligence-driven forecasting and shift optimization for pediatric emergency department crowding

The AI-driven forecasting and shift optimization system demonstrated the efficacy of integrating AI and MLOps in predicting PED overcrowding and optimizing physician shifts. This approach outperformed traditional methods, highlighting its potential for managing overcrowding in emergency departments. Future research should focus on multicenter validation and real-world implementation to fully leverage the benefits of this innovative system.

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Publication Details

Journal
JAMIA Open
Published
2025-03-06
DOI
https://doi.org/10.1093/jamiaopen/ooae138
Citations
11
Primary Topic
Emergency and Acute Care Studies
Type
article
Field-Weighted Citation Impact
24.79
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article

Artificial intelligence-driven forecasting and shift optimization for pediatric emergency department crowding

Özlem Tekşam, Izzet Turkalp Akbasli, Ahmet Ziya Bırbılen
11 citations
JAMIA Open
Emergency and Acute Care Studies
24.79
article

Artificial intelligence-driven forecasting and shift optimization for pediatric emergency department crowding

Özlem Tekşam, Izzet Turkalp Akbasli, Ahmet Ziya Bırbılen
article en
11 citations

Abstract

The AI-driven forecasting and shift optimization system demonstrated the efficacy of integrating AI and MLOps in predicting PED overcrowding and optimizing physician shifts. This approach outperformed traditional methods, highlighting its potential for managing overcrowding in emergency departments. Future research should focus on multicenter validation and real-world implementation to fully leverage the benefits of this innovative system.

JAMIA OpenVol. 8(2)
Hacettepe University (TR)
Openalex Percentile: Top 0%
Emergency and Acute Care Studies
24.79
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