Comparison of machine learning methods for prediction of osteoradionecrosis incidence in patients with head and neck cancer


Humbert-Vidan L., Patel V., Oksuz I., King A. P., Urbano T. G.

BRITISH JOURNAL OF RADIOLOGY, cilt.94, sa.1120, 2021 (SCI-Expanded) identifier identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 94 Sayı: 1120
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1259/bjr.20200026
  • Dergi Adı: BRITISH JOURNAL OF RADIOLOGY
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, CAB Abstracts, CINAHL, EMBASE, MEDLINE, Veterinary Science Database
  • İstanbul Teknik Üniversitesi Adresli: Evet

Özet

Objectives: Mandible osteoradionecrosis (ORN) is one of the most severe toxicities in patients with head and neck cancer (HNC) undergoing radiotherapy (RT). The existing literature focuses on the correlation of mandible ORN and clinical and dosimetric factors. This study proposes the use of machine learning (ML) methods as prediction models for mandible ORN incidence.