Predicting the Local Response of Esophageal Squamous Cell Carcinoma to Neoadjuvant Chemoradiotherapy by Radiomics with a Machine Learning Method Using (18)F-FDG PET Images

Lignende værker

• Long-term outcomes of induction chemotherapy followed by chemoradiotherapy using volumetric-modulated arc therapy as an organ preservation approach in patients with stage IVA-B oropharyngeal or hypopharyngeal cancers
  af: Kubo, Katsumaro, et al.
  Udgivet: (2020)
• Long-term results of definitive chemoradiotherapy for unresectable locally advanced esophageal squamous cell carcinoma
  af: Ochi, Masanori, et al.
  Udgivet: (2020)
• Analysis of cardiac toxicity after definitive chemoradiotherapy for esophageal cancer using a biological dose–volume histogram
  af: Takeuchi, Yuki, et al.
  Udgivet: (2020)
• Long-term results of neoadjuvant chemoradiotherapy using cisplatin and 5-fluorouracil followed by esophagectomy for resectable, locally advanced esophageal squamous cell carcinoma
  af: Murakami, Yuji, et al.
  Udgivet: (2018)
• Radiomics-based decision support tool with ground-glass opacity status of 5-year survival prediction for early-stage non-small cell lung cancer
  af: Reo Isobe, et al.
  Udgivet: (2025-10-01)