Value of handcrafted and deep radiomic features towards training robust machine learning classifiers for prediction of prostate cancer disease aggressiveness

There is a growing piece of evidence that artificial intelligence may be helpful in the entire prostate cancer disease continuum. However, building machine learning algorithms robust to inter- and intra-radiologist segmentation variability is still a challenge. With this goal in mind, several model...

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Detalles Bibliográficos
Autores principales: Rodrigues, Ana, Rodrigues, Nuno, Santinha, João, Lisitskaya, Maria V., Uysal, Aycan, Matos, Celso, Domingues, Inês, Papanikolaou, Nickolas
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/PMC10110526/
https://www.ncbi.nlm.nih.gov/pubmed/37069257
http://dx.doi.org/10.1038/s41598-023-33339-0

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10110526/
https://www.ncbi.nlm.nih.gov/pubmed/37069257
http://dx.doi.org/10.1038/s41598-023-33339-0

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