Probing the rules of cell coordination in live tissues by interpretable machine learning based on graph neural networks.
Takaki YamamotoKatie CockburnValentina GrecoKyogo KawaguchiPublished in: PLoS Comput. Biol. (2022)
Keyphrases
- medical imaging
- machine learning
- neural network
- medical images
- rule extraction
- pattern recognition
- image analysis
- classification rules
- learning classifier systems
- learning algorithm
- trained neural networks
- learning rules
- cooperative
- knowledge representation
- machine learning algorithms
- structured data
- graph model
- feature selection
- machine learning methods
- graph matching
- information sharing
- graph representation
- data mining
- decision trees
- data analysis
- information extraction
- random walk
- graph theory
- directed graph
- fuzzy logic
- rule learning
- genetic algorithm
- knowledge acquisition
- association rules
- supervised learning
- artificial intelligence
- bipartite graph
- reinforcement learning
- hidden units
- multiple agents
- social networks
- knowledge base
- histopathological images
- graph databases
- directed acyclic graph
- fuzzy systems
- inductive learning
- recurrent neural networks
- multi agent
- inductive logic programming
- rule sets
- self organizing maps
- association rule mining
- back propagation
- text classification