Interpretability of radiomics models is improved when using feature group selection strategies for predicting molecular and clinical targets in clear-cell renal cell carcinoma: insights from the TRACERx Renal study

BACKGROUND: The aim of this work is to evaluate the performance of radiomics predictions for a range of molecular, genomic and clinical targets in patients with clear cell renal cell carcinoma (ccRCC) and demonstrate the impact of novel feature selection strategies and sub-segmentations on model int...

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Detalles Bibliográficos
Autores principales: Orton, Matthew R., Hann, Evan, Doran, Simon J., Shepherd, Scott T. C., Ap Dafydd, Derfel, Spencer, Charlotte E., López, José I., Albarrán-Artahona, Víctor, Comito, Francesca, Warren, Hannah, Shur, Joshua, Messiou, Christina, Larkin, James, Turajlic, Samra, Koh, Dow-Mu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424427/
https://www.ncbi.nlm.nih.gov/pubmed/37580840
http://dx.doi.org/10.1186/s40644-023-00594-3

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10424427/
https://www.ncbi.nlm.nih.gov/pubmed/37580840
http://dx.doi.org/10.1186/s40644-023-00594-3

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