Ovarian recurrence risk assessment using machine learning, clinical information, and serum protein levels to predict survival in high grade ovarian cancer

In ovarian cancer, there is no current method to accurately predict recurrence after a complete response to chemotherapy. Here, we develop a machine learning risk score using serum proteomics for the prediction of early recurrence of ovarian cancer after initial treatment. The developed risk score w...

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Detalles Bibliográficos
Autores principales: Mysona, David P., Purohit, Sharad, Richardson, Katherine P., Suhner, Jessa, Brzezinska, Bogna, Rungruang, Bunja, Hopkins, Diane, Bearden, Gregory, Higgins, Robert, Johnson, Marian, Bin Satter, Khaled, McIndoe, Richard, Ghamande, Sharad
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/PMC10684567/
https://www.ncbi.nlm.nih.gov/pubmed/38016985
http://dx.doi.org/10.1038/s41598-023-47983-z

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10684567/
https://www.ncbi.nlm.nih.gov/pubmed/38016985
http://dx.doi.org/10.1038/s41598-023-47983-z

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