Evaluation of acute hematological toxicity by machine learning in gynecologic cancers using postoperative radiotherapy.
Indian journal of cancer, cilt.59, sa.2, ss.178-186, 2022 (SCI-Expanded, Scopus)
- Yayın Türü: Makale / Tam Makale
- Cilt numarası: 59 Sayı: 2
- Basım Tarihi: 2022
- Doi Numarası: 10.4103/ijc.ijc_666_19
- Dergi Adı: Indian journal of cancer
- Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, CINAHL, EMBASE, MEDLINE, Veterinary Science Database
- Sayfa Sayıları: ss.178-186
- Anahtar Kelimeler: Cancer, machine learning, radiotherapy, toxicity, INTENSITY-MODULATED RADIOTHERAPY, BONE-MARROW, RADIATION-THERAPY, CERVICAL-CANCER, MALIGNANCIES, PREDICTORS, VOLUME, IMRT, ARC
- Eskişehir Osmangazi Üniversitesi Adresli: Evet
Özet
Background: The aim of the study is to investigate the factors affecting acute hematologic toxicity (HT) in the adjuvant radiotherapy (RT) of gynecologic cancers by machine learning.