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Analysing repeated hospital readmissions using data mining techniques
Few studies have examined how to identify future readmission of patients with a large number of repeat emergency department (ED) visits. We explore 30-day readmission risk prediction using Microsoft’s AZURE machine learning software and compare five classification methods: Logistic Regression, Boost...
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| Published in: | Health Syst (Basingstoke) |
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| Main Authors: | , |
| Format: | Artigo |
| Language: | Inglês |
| Published: |
Taylor & Francis
2017
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| Subjects: | |
| Online Access: | https://ncbi.nlm.nih.gov/pmc/articles/PMC6452839/ https://ncbi.nlm.nih.gov/pubmed/31214343 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/20476965.2017.1390635 |
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