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...

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Detalles Bibliográficos
Autores principales: Tschodu, Dimitrij, Lippoldt, Jürgen, Gottheil, Pablo, Wegscheider, Anne-Sophie, Käs, Josef A., Niendorf, Axel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2023
Materias:
Article
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

Internet

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

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