Investigation of Radiation-Induced Toxicity in Head and Neck Cancer Patients through Radiomics and Machine Learning: A Systematic Review.
Roberta CarbonaraPierluigi BonomoAlessia Di RitoVittorio DidonnaFabiana GregucciMaria Paola CilibertiAlessia SurgoIlaria BonaparteAlba FiorentinoAngela SardaroPublished in: Journal of oncology (2021)
Published radiomic studies provide encouraging but still limited and preliminary data that require further validation to improve the decision-making processes in preventing and managing radiation-induced toxicities.
Keyphrases
- radiation induced
- radiation therapy
- machine learning
- end stage renal disease
- decision making
- ejection fraction
- newly diagnosed
- chronic kidney disease
- big data
- oxidative stress
- peritoneal dialysis
- artificial intelligence
- randomized controlled trial
- electronic health record
- magnetic resonance imaging
- squamous cell carcinoma
- systematic review
- lymph node metastasis
- computed tomography
- patient reported outcomes
- magnetic resonance
- deep learning
- contrast enhanced