Relation extraction from clinical texts using domain invariant convolutional neural network

Understand

In recent years extracting relevant information from biomedical and clinical texts such as research articles, discharge summaries, or electronic health records have been a subject of many research efforts and shared challenges.

• Relation extraction is the process of detecting and classifying the semantic relation among entities in a given piece of texts.
• Existing models for this task in biomedical domain use either manually engineered features or kernel methods to create feature vector.
• These features are then fed to classifier for the prediction of the correct class.