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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...
Autores principales: | Gangil, Tarun, Sharan, Krishna, Rao, B. Dinesh, Palanisamy, Krishnamoorthy, Chakrabarti, Biswaroop, Kadavigere, Rajagopal |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
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 |
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