A principled machine learning framework improves accuracy of stage II colorectal cancer prognosis

Accurate prognosis is fundamental in planning an appropriate therapy for cancer patients. Consequent to the heterogeneity of the disease, intra- and inter-pathologist variability, and the inherent limitations of current pathological reporting systems, patient outcome varies considerably within simil...

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Detalles Bibliográficos
Autores principales: Dimitriou, Neofytos, Arandjelović, Ognjen, Harrison, David J., Caie, Peter D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550189/
https://www.ncbi.nlm.nih.gov/pubmed/31304331
http://dx.doi.org/10.1038/s41746-018-0057-x

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6550189/
https://www.ncbi.nlm.nih.gov/pubmed/31304331
http://dx.doi.org/10.1038/s41746-018-0057-x

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