Predicting Hospital Length of Stay (PHLOS): A Multi-tiered Data Mining Approach-Reference-Cited by-同舟云学术

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Predicting Hospital Length of Stay (PHLOS): A Multi-tiered Data Mining Approach

Published:2012-12 Issue: Volume: Page:
ISSN:
Container-title:2012 IEEE 12th International Conference on Data Mining Workshops
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Author:

Azari Ali,Janeja Vandana P.,Mohseni Alex

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx5/6403636/6406400/06406418.pdf?arnumber=6406418

Cited by 25 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Hybrid Summarization of Medical Records for Predicting Length of Stay in the Intensive Care Unit;Applied Sciences;2024-07-03

2. A Granular View of Emergency Department Length of Stay: Improving Predictive Power and Extracting Real-Time, Actionable Insights;Annals of Emergency Medicine;2024-03

3. A prescriptive optimization approach to identification of minimal barriers for surgical patients;2023-03-29

4. Optimizing Medical Healthcare Services Using Big Data Analytics;2023 9th International Conference on Advanced Computing and Communication Systems (ICACCS);2023-03-17

5. Major areas of interest of artificial intelligence research applied to health care administrative data: a scoping review;Frontiers in Pharmacology;2022-07-18

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