Simplifying clinical use of TCGA molecular subtypes through machine learning models Editorial
| Authors: | Boehm, K. M.; Sánchez-Vega, F. |
| Title: | Simplifying clinical use of TCGA molecular subtypes through machine learning models |
| Abstract: | In this issue of Cancer Cell, Ellrott et al. present machine learning models to classify samples into The Cancer Genome Atlas molecular subtypes using compact sets of genomic features. These validated, ready-to-use models are publicly available, although some clinical hurdles need to be cleared before they are fully implemented. © 2024 Elsevier Inc. |
| Keywords: | note; microrna; dna methylation; cancer cell; cancer classification; machine learning; cancer prognosis; dna sequencing; human; oncogenomics |
| Journal Title: | Cancer Cell |
| Volume: | 43 |
| Issue: | 2 |
| ISSN: | 1535-6108 |
| Publisher: | Cell Press |
| Date Published: | 2025-02-10 |
| Start Page: | 166 |
| End Page: | 168 |
| Language: | English |
| DOI: | 10.1016/j.ccell.2024.12.009 |
| PUBMED: | 39824177 |
| PROVIDER: | scopus |
| DOI/URL: | |
| Notes: | Note -- Source: Scopus |
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