ロード中...
A Machine-Learning Tool Concurrently Models Single Omics and Phenome Data for Functional Subtyping and Personalized Cancer Medicine
One of the major challenges in defining clinically-relevant and less heterogeneous tumor subtypes is assigning biological and/or clinical interpretations to etiological (intrinsic) subtypes. Conventional clustering/subtyping approaches often fail to define such subtypes, as they involve several disc...
保存先:
| 主要な著者: | , , , , |
|---|---|
| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
MDPI AG
2020-09-01
|
| シリーズ: | Cancers |
| 主題: | |
| オンライン･アクセス: | https://www.mdpi.com/2072-6694/12/10/2811 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|