Deep versus Handcrafted Tensor Radiomics Features: Prediction of Survival in Head and Neck Cancer Using Machine Learning and Fusion Techniques.

Salmanpour, Mohammad R; Rezaeijo, Seyed Masoud; Hosseinzadeh, Mahdi; Rahmim, Arman

Salmanpour, Mohammad R; Rezaeijo, Seyed Masoud; Hosseinzadeh, Mahdi; Rahmim, Arman.

Afiliação

Salmanpour MR; Department of Integrative Oncology, BC Cancer Research Institute, Vancouver, BC V5Z 1L3, Canada.
Rezaeijo SM; Technological Virtual Collaboration (TECVICO CORP.), Vancouver, BC V5E 3J7, Canada.
Hosseinzadeh M; Department of Medical Physics, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz 6135715794, Iran.
Rahmim A; Technological Virtual Collaboration (TECVICO CORP.), Vancouver, BC V5E 3J7, Canada.

Diagnostics (Basel) ; 13(10)2023 May 11.

Article em En | MEDLINE | ID: mdl-37238180

Palavras-chave

deep learning algorithms; deep learning features; head and neck squamous cell carcinomas; hybrid machine learning methods; progression-free survival; radiomic features

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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Canadá

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