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Prediction models for acute kidney injury in patients with gastrointestinal cancers: a real-world study based on Bayesian networks
BACKGROUND: This study attempts to establish a Bayesian networks (BNs) based model for inferring the risk of AKI in gastrointestinal cancer (GI) patients, and to compare its predictive capacity with other machine learning (ML) models. METHODS: From 1 October 2014 to 30 September 2015, we recruited 6...
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| Wydane w: | Ren Fail |
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| Główni autorzy: | , , , , , , , |
| Format: | Artigo |
| Język: | Inglês |
| Wydane: |
Taylor & Francis
2020
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| Hasła przedmiotowe: | |
| Dostęp online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7472473/ https://ncbi.nlm.nih.gov/pubmed/32838613 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1080/0886022X.2020.1810068 |
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