Prediction of carcinogenic human papillomavirus types in cervical cancer from multiparametric magnetic resonance images with machine learning-based radiomics models.
Okan İnceEmre UysalGörkem DurakSuzan Deniz ÖnolBinnur Dönmez YılmazŞükrü Mehmet ErtürkHakan ÖnderPublished in: Diagnostic and interventional radiology (Ankara, Turkey) (2022)
Machine learning-based radiomics models based on pre-treatment MRI can detect carcinogenic HPV status with discriminative accuracy.
Keyphrases
- machine learning
- contrast enhanced
- magnetic resonance
- deep learning
- magnetic resonance imaging
- artificial intelligence
- lymph node metastasis
- polycyclic aromatic hydrocarbons
- big data
- computed tomography
- convolutional neural network
- diffusion weighted imaging
- high grade
- optical coherence tomography
- squamous cell carcinoma
- combination therapy