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Multimodality deep learning radiomics nomogram for preoperative prediction of malignancy of breast cancer: a multicenter study.
Wu, Peiyan; Jiang, Yan; Xing, Hanshuo; Song, Wenbo; Cui, Xinwu; Wu, Xing Long; Xu, Guoping.
Affiliation
  • Wu P; School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, People's Republic of China.
  • Jiang Y; School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, People's Republic of China.
  • Xing H; School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, People's Republic of China.
  • Song W; School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, People's Republic of China.
  • Cui X; Department of Medical Ultrasound, Tongji Hospital of Tongji Medical College, Huazhong University of Science and Technology, Wuhan, People's Republic of China.
  • Wu XL; School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, People's Republic of China.
  • Xu G; School of Computer Science and Engineering, Hubei Key Laboratory of Intelligent Robot, Wuhan Institute of Technology, Wuhan, People's Republic of China.
Phys Med Biol ; 68(17)2023 08 18.
Article in En | MEDLINE | ID: mdl-37524093
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Deep Learning Type of study: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Phys Med Biol Year: 2023 Document type: Article
Fulltext
Add to My VHL
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Breast Neoplasms / Deep Learning Type of study: Clinical_trials / Observational_studies / Prognostic_studies / Risk_factors_studies Limits: Female / Humans Language: En Journal: Phys Med Biol Year: 2023 Document type: Article