Utility of adding Radiomics to clinical features in predicting the outcomes of radiotherapy for head and neck cancer using machine learning

BACKGROUND: Radiomics involves the extraction of quantitative information from annotated Computed-Tomography (CT) images, and has been used to predict outcomes in Head and Neck Squamous Cell Carcinoma (HNSCC). Subjecting combined Radiomics and Clinical features to Machine Learning (ML) could offer b...

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Detalles Bibliográficos
Autores principales: Gangil, Tarun, Sharan, Krishna, Rao, B. Dinesh, Palanisamy, Krishnamoorthy, Chakrabarti, Biswaroop, Kadavigere, Rajagopal
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754241/
https://www.ncbi.nlm.nih.gov/pubmed/36520945
http://dx.doi.org/10.1371/journal.pone.0277168

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9754241/
https://www.ncbi.nlm.nih.gov/pubmed/36520945
http://dx.doi.org/10.1371/journal.pone.0277168

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