Development and Testing of a Machine Learning Model Using (18)F-Fluorodeoxyglucose PET/CT-Derived Metabolic Parameters to Classify Human Papillomavirus Status in Oropharyngeal Squamous Carcinoma

OBJECTIVE: To develop and test a machine learning model for classifying human papillomavirus (HPV) status of patients with oropharyngeal squamous cell carcinoma (OPSCC) using (18)F-fluorodeoxyglucose ((18)F-FDG) PET-derived parameters in derived parameters and an appropriate combination of machine l...

Descripción completa

Detalles Bibliográficos
Autores principales: Woo, Changsoo, Jo, Kwan Hyeong, Sohn, Beomseok, Park, Kisung, Cho, Hojin, Kang, Won Jun, Kim, Jinna, Lee, Seung-Koo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Korean Society of Radiology 2023
Materias:
Neuroimaging and Head & Neck
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830147/
https://www.ncbi.nlm.nih.gov/pubmed/36606620
http://dx.doi.org/10.3348/kjr.2022.0397

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9830147/
https://www.ncbi.nlm.nih.gov/pubmed/36606620
http://dx.doi.org/10.3348/kjr.2022.0397

Ejemplares similares