Machine learning and magnetic resonance imaging radiomics for predicting human papilloma virus status and prognostic factors in oropharyngeal squamous cell carcinoma.
Young Min ParkJae-Yol LimYoon Woo KohSe-Heon KimEun Chang ChoiPublished in: Head & neck (2022)
A machine learning model using MRI radiomics showed satisfactory performance in predicting pathologic factors and treatment outcomes of OPSCC patients.
Keyphrases
- prognostic factors
- machine learning
- magnetic resonance imaging
- contrast enhanced
- squamous cell carcinoma
- lymph node metastasis
- end stage renal disease
- endothelial cells
- ejection fraction
- newly diagnosed
- artificial intelligence
- chronic kidney disease
- computed tomography
- neoadjuvant chemotherapy
- magnetic resonance
- diffusion weighted imaging
- radiation therapy
- deep learning
- patient reported outcomes
- induced pluripotent stem cells
- pluripotent stem cells
- patient reported