Prediction of Survival and Recurrence Patterns by Machine Learning in Gastric Cancer Cases Undergoing Radiation Therapy and Chemotherapy

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AKÇAY M. Ç., ETİZ D., çelik Ö.

ADVANCES IN RADIATION ONCOLOGY, cilt.5, sa.6, ss.1179-1187, 2020 (ESCI) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 5 Sayı: 6
  • Basım Tarihi: 2020
  • Doi Numarası: 10.1016/j.adro.2020.07.007
  • Dergi Adı: ADVANCES IN RADIATION ONCOLOGY
  • Derginin Tarandığı İndeksler: Emerging Sources Citation Index (ESCI), Scopus
  • Sayfa Sayıları: ss.1179-1187
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

Purpose: Radical surgery is the most important treatment modality in gastric cancer. Preoperative or postoperative radiation therapy (RT) and perioperative chemotherapy are the treatment options that should be added to surgery. This study aimed to evaluate the overall survival (OS) and recurrence patterns by machine learning in gastric cancer cases undergoing RT.