CIMIL-CRC: a clinically-informed multiple instance learning framework for patient-level colorectal cancer molecular subtypes classification from H\&E stained images.
Hadar HeziMatan GelberAlexander BalabanovYosef E. MaruvkaMoti FreimanPublished in: CoRR (2024)
Keyphrases
- multiple instance learning
- image categorization
- object based image retrieval
- image annotation
- supervised learning
- multiple instance
- image classification
- multi class
- class labels
- colorectal cancer
- image understanding
- semi supervised
- image recognition
- image collections
- classification accuracy
- decision trees
- small number
- image database
- image data
- object recognition
- diverse density
- learning algorithm
- semi supervised learning
- image features
- image analysis
- support vector
- image processing
- text categorization
- visual features
- unsupervised learning
- image search
- active learning
- image retrieval
- skin lesion
- feature extraction