Art
J-GLOBAL ID:202002211200813831   Reference number:20A2769185

Identification of a Transcriptomic Prognostic Signature by Machine Learning Using a Combination of Small Cohorts of Prostate Cancer

前立腺癌の小コホートの組合せを用いた機械学習によるトランスクリプトーム予後シグネチャの同定【JST・京大機械翻訳】
Author (14):
Material:
Volume: 11  Page: 550894  Publication year: 2020 
JST Material Number: U7071A  ISSN: 1664-8021  Document type: Article
Article type: 原著論文  Country of issue: Switzerland (CHE)  Language: ENGLISH (EN)
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JST classification
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Urogenital tumors(=neoplasms) 
Reference (98):
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  • Al-JarrahO. Y.YooP. D.MuhaidatS.KaragiannidisG. K.TahaK. (2015). Efficient machine learning for big data: a review. Big Data Res. 2 87-93. doi: 10.1016/j.bdr.2015.04.001
  • AlmeidaH.MeursM.-J.KosseimL.ButlerG.TsangA. (2014). Machine learning for biomedical literature triage. PLoS One 9:e115892. doi: 10.1371/journal.pone.0115892 25551575
  • AminM. B.EdgeS. B.GreeneF. L.ByrdD. R.BrooklandR. K.WashingtonM. K. (2018). AJCC Cancer Staging Manual. Berlin: Springer.
  • AndrewsS.KruegerF.Segonds-PichonA.BigginsL.KruegerC.WingettS. (2010). FastQC: A Quality Control Tool for High Throughput Sequence Data. Babraham: Babraham Institute.
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