Assessing Axillary Lymph Node Burden and Prognosis in cT1‐T2 Stage Breast Cancer Using Machine Learning Methods: A Retrospective Dual‐Institutional MRI Study

Documenti analoghi

• MRI ‐Based Radiomics Model for Classifying Axillary Lymph Node Burden and Disease‐Free Survival in Patients With Early‐Stage Breast Cancer
  di: Yulan Tong, et al.
  Pubblicazione: (2025)
• MRI‐Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN‐RNN Model
  di: Yi‐Jun Guo, et al.
  Pubblicazione: (2024)
• Habitat Radiomics Based on Dynamic Contrast‐Enhanced Magnetic Resonance Imaging for Assessing Axillary Lymph Node Burden in Clinical T1–T2 Stage Breast Cancer: A Multicenter and Interpretable Study
  di: Siyi Chen, et al.
  Pubblicazione: (2025)
• Editorial for “MRI‐Based Kinetic Heterogeneity Evaluation in the Accurate Access of Axillary Lymph Node Status in Breast Cancer Using a Hybrid CNN‐RNN Model”
  di: Endre Grøvik
  Pubblicazione: (2024)
• Intra‐ and Peri‐tumoral Radiomics Based on Dynamic Contrast Enhanced‐MRI to Identify Lymph Node Metastasis and Prognosis in Intrahepatic Cholangiocarcinoma
  di: Yi‐Jun Pan, et al.
  Pubblicazione: (2024)