Deep Radiogenomics of Lower-Grade Gliomas: Convolutional Neural Networks Predict Tumor Genomic Subtypes Using MR Images.
Mateusz BudaEhab A AlBadawyAshirbani SahaMaciej A MazurowskiPublished in: Radiology. Artificial intelligence (2020)
These findings show the potential of utilizing deep learning to identify relationships between cancer imaging and cancer genomics in LGGs. However, more accurate models are needed to justify clinical use of such tools, which might be obtained using substantially larger training datasets.Supplemental material is available for this article.© RSNA, 2020.
Keyphrases
- convolutional neural network
- deep learning
- papillary thyroid
- squamous cell
- high resolution
- artificial intelligence
- high grade
- magnetic resonance
- lymph node metastasis
- computed tomography
- gene expression
- squamous cell carcinoma
- magnetic resonance imaging
- risk assessment
- copy number
- childhood cancer
- contrast enhanced
- photodynamic therapy
- rna seq