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Re-evaluation of publicly available gene-expression databases using machine-learning yields a maximum prognostic power in breast cancer
Gene expression signatures refer to patterns of gene activities and are used to classify different types of cancer, determine prognosis, and guide treatment decisions. Advancements in high-throughput technology and machine learning have led to improvements to predict a patient’s prognosis for differ...
| Autores principales: | , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10556090/ https://www.ncbi.nlm.nih.gov/pubmed/37798300 http://dx.doi.org/10.1038/s41598-023-41090-9 |