Radiomic and Genomic Machine Learning Method Performance for Prostate Cancer Diagnosis: Systematic Literature Review

BACKGROUND: Machine learning algorithms have been drawing attention at the joining of pathology and radiology in prostate cancer research. However, due to their algorithmic learning complexity and the variability of their architecture, there is an ongoing need to analyze their performance. OBJECTIVE...

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Detalles Bibliográficos
Autores principales: Castaldo, Rossana, Cavaliere, Carlo, Soricelli, Andrea, Salvatore, Marco, Pecchia, Leandro, Franzese, Monica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2021
Materias:
Review
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050752/
https://www.ncbi.nlm.nih.gov/pubmed/33792552
http://dx.doi.org/10.2196/22394

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8050752/
https://www.ncbi.nlm.nih.gov/pubmed/33792552
http://dx.doi.org/10.2196/22394

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