Litcius/Paper detail

Effect of machine learning re-sampling techniques for imbalanced datasets in 18F-FDG PET-based radiomics model on prognostication performance in cohorts of head and neck cancer patients

Chenyi Xie, Richard Du, Joshua W. K. Ho, Herbert Pang, K.W. Chiu, Elaine Lee, Varut Vardhanabhuti

2020European Journal of Nuclear Medicine and Molecular Imaging98 citationsDOI

Topics & Concepts

OversamplingUndersamplingRadiomicsArtificial intelligenceMachine learningSampling (signal processing)MedicineNasopharyngeal carcinomaComputer scienceRadiologyRadiation therapyFilter (signal processing)Bandwidth (computing)Computer networkComputer visionRadiomics and Machine Learning in Medical ImagingHead and Neck Cancer StudiesInflammatory Biomarkers in Disease Prognosis
Effect of machine learning re-sampling techniques for imbalanced datasets in 18F-FDG PET-based radiomics model on prognostication performance in cohorts of head and neck cancer patients | Litcius