Multimodality radiomics for tumor prognosis in nasopharyngeal carcinoma.
Sararas KhongwirotphanSornjarod OonsiriSarin KitpanitAnussara PrayongratDanita KannarunimitChakkapong ChakkabatChawalit LertbutsayanukulSira SriswasdiYothin RakvongthaiPublished in: PloS one (2024)
The combination of multimodality radiomic features from CT and MR images could offer superior predictive performance for OS, PFS, and DMFS compared to relying on conventional clinical data alone.
Keyphrases
- contrast enhanced
- magnetic resonance imaging
- computed tomography
- magnetic resonance
- deep learning
- electronic health record
- convolutional neural network
- image quality
- dual energy
- big data
- lymph node metastasis
- optical coherence tomography
- positron emission tomography
- squamous cell carcinoma
- machine learning
- artificial intelligence