A pretreatment multiparametric MRI ‐based radiomics‐clinical machine learning model for predicting radiation‐induced temporal lobe injury in patients with nasopharyngeal carcinoma

Documenti analoghi

• Mecapegfilgrastim for the prophylaxis of chemotherapy‐induced neutropenia in locally advanced nasopharyngeal carcinoma: A prospective phase II clinical study
  di: Qifeng Jin, et al.
  Pubblicazione: (2024)
• Lachnoclostridium intestinal flora is associated with immunotherapy efficacy in nasopharyngeal carcinoma
  di: Zikun Yu, et al.
  Pubblicazione: (2024)
• The prevalence of gastroesophageal reflux disease and laryngopharyngeal reflux in patients with dysphagia after radiotherapy for nasopharyngeal carcinoma
  di: Peter K. M. Ku, et al.
  Pubblicazione: (2024)
• Evaluating the reduction of elective radiotherapy fields for de novo metastatic nasopharyngeal carcinoma in the immunotherapy era
  di: Ting Jin, et al.
  Pubblicazione: (2024)
• Predicting the overall survival and progression‐free survival of nasopharyngeal carcinoma patients based on hemoglobin, albumin, and globulin ratio and classical clinicopathological parameters
  di: Zui Chen, et al.
  Pubblicazione: (2024)