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Machine Learning Predicts Pathologic Complete Response to Neoadjuvant Chemotherapy for ER+HER2- Breast Cancer: Integrating Tumoral and Peritumoral MRI Radiomic Features.
Park, Jiwoo; Kim, Min Jung; Yoon, Jong-Hyun; Han, Kyunghwa; Kim, Eun-Kyung; Sohn, Joo Hyuk; Lee, Young Han; Yoo, Yangmo.
Afiliación
  • Park J; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Kim MJ; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Yoon JH; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Han K; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Kim EK; Department of Radiology, Research Institute of Radiological Science, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin-si 06230, Republic of Korea.
  • Sohn JH; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Lee YH; Department of Radiology and Research Institute of Radiological Science, Severance Hospital, Yonsei University College of Medicine, Seoul 03722, Republic of Korea.
  • Yoo Y; Department of Electronic Engineering, Sogang University, Seoul 04107, Republic of Korea.
Diagnostics (Basel) ; 13(19)2023 Sep 23.
Article en En | MEDLINE | ID: mdl-37835774
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diagnostics (Basel) Año: 2023 Tipo del documento: Article Pais de publicación: Suiza
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Diagnostics (Basel) Año: 2023 Tipo del documento: Article Pais de publicación: Suiza