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Unsupervised machine learning and prognostic factors of survival in chronic lymphocytic leukemia
OBJECTIVE: Unsupervised machine learning approaches hold promise for large-scale clinical data. However, the heterogeneity of clinical data raises new methodological challenges in feature selection, choosing a distance metric that captures biological meaning, and visualization. We hypothesized that...
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| 出版年: | J Am Med Inform Assoc |
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| 主要な著者: | , , , , |
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
Oxford University Press
2020
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| 主題: | |
| オンライン･アクセス: | https://ncbi.nlm.nih.gov/pmc/articles/PMC7647286/ https://ncbi.nlm.nih.gov/pubmed/32483590 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1093/jamia/ocaa060 |
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