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Combined unsupervised-supervised machine learning for phenotyping complex diseases with its application to obstructive sleep apnea
Unsupervised clustering models have been widely used for multimetric phenotyping of complex and heterogeneous diseases such as diabetes and obstructive sleep apnea (OSA) to more precisely characterize the disease beyond simplistic conventional diagnosis standards. However, the number of clusters and...
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| 發表在: | Sci Rep |
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| Main Authors: | , , , , , |
| 格式: | Artigo |
| 語言: | Inglês |
| 出版: |
Nature Publishing Group UK
2021
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| 主題: | |
| 在線閱讀: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7904925/ https://ncbi.nlm.nih.gov/pubmed/33627761 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1038/s41598-021-84003-4 |
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