Deep learning radiomics of multimodal ultrasound for classifying metastatic cervical lymphadenopathy into primary cancer sites: a feasibility study.

Zhu, Yangyang; Meng, Zheling; Wu, Hao; Fan, Xiao; Lv, Wenhao; Tian, Jie; Wang, Kun; Nie, Fang

Deep learning radiomics of multimodal ultrasound for classifying metastatic cervical lymphadenopathy into primary cancer sites: a feasibility study.

Zhu, Yangyang; Meng, Zheling; Wu, Hao; Fan, Xiao; Lv, Wenhao; Tian, Jie; Wang, Kun; Nie, Fang.

Afiliação

Zhu Y; Medical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Meng Z; CAS Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Wu H; CAS Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.
Fan X; School of Artificial Intelligence, University of the Chinese Academy of Sciences School, Beijing, China.
Lv W; Medical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Tian J; Medical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Wang K; Medical Center of Ultrasound, Lanzhou University Second Hospital, Lanzhou, China.
Nie F; CAS Key Laboratory of Molecular Imaging, The State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China.

Ultraschall Med ; 2023 Dec 05.

Article em En | MEDLINE | ID: mdl-38052240

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Texto completo: 1 Coleções: 01-internacional Temas: Geral / Tipos_de_cancer / Outros_tipos Base de dados: MEDLINE Idioma: En Revista: Ultraschall Med Ano de publicação: 2023 Tipo de documento: Article País de afiliação: China

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