Machine Learning Methods in Classification of Prolonged Radiation Therapy in Oropharyngeal Cancer: National Cancer Database.
Seungjun AhnEun Jeong OhMatthew I SaleemTristan ThamPublished in: Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery (2024)
Our assessment of various ML techniques showed that RF was superior to traditional logistic regression at classifying OPSCC patients at risk of prolonged RTD. Application of such algorithms may have potential to identify high risk patients and enable early interventions to improve survival.
Keyphrases
- machine learning
- radiation therapy
- deep learning
- end stage renal disease
- ejection fraction
- newly diagnosed
- artificial intelligence
- papillary thyroid
- big data
- prognostic factors
- emergency department
- risk assessment
- patient reported outcomes
- young adults
- squamous cell
- human health
- patient reported
- lymph node metastasis
- clinical evaluation