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.

Afiliación

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 en En | MEDLINE | ID: mdl-37238180

Palabras clave

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 Colección: 01-internacional Base de datos: MEDLINE Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Diagnostics (Basel) Año: 2023 Tipo del documento: Article País de afiliación: Canadá Pais de publicación: Suiza

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