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Selecting the best machine learning algorithm to support the diagnosis of Non-Alcoholic Fatty Liver Disease: A meta learner study
BACKGROUND & AIMS: Liver ultrasound scan (US) use in diagnosing Non-Alcoholic Fatty Liver Disease (NAFLD) causes costs and waiting lists overloads. We aimed to compare various Machine learning algorithms with a Meta learner approach to find the best of these as a predictor of NAFLD. METHODS: The...
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| Pubblicato in: | PLoS One |
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| Autori principali: | , , , , , , , , , , , , , , |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Public Library of Science
2020
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7575109/ https://ncbi.nlm.nih.gov/pubmed/33079971 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1371/journal.pone.0240867 |
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