Habitat clustering of ultrasound images of breast cancer is effectively supported by the combined implementation of the L1,2-norm and FCNN algorithms, allowing for the accurate classification of the Ki-67 status in breast cancer patients.
Keyphrases
- deep learning
- neural network
- machine learning
- magnetic resonance imaging
- neoadjuvant chemotherapy
- primary care
- climate change
- healthcare
- convolutional neural network
- single cell
- high resolution
- optical coherence tomography
- squamous cell carcinoma
- quality improvement
- rna seq
- magnetic resonance
- computed tomography
- lymph node
- childhood cancer