Result description
We have developed Deep Learning methods for: Knowledge Graph Completion and Embeddings, Named Entity framework based on transfer learning (called T2NER), MedDistant19, MEDDISTANT19, a benchmark for broad-coverage biomedical relation extraction, a method for few-shot cross-lingual transfer for coarse-grained de-identification of code-mixed clinical texts.
Addressing target audiences and expressing needs
- We are sharing our knowledge
We are looking for research institutes (academia and industry) who are interested in exploring and developing NLP and Machine Learning for digitalisation and machine understanding of clinical text in order to support future interaction and communication with and about information in the e-Health are.
- Others/ No specific audience
- Research and Technology Organisations
R&D, Technology and Innovation aspects
Available software package and data via github for LowerFER, T2NER, MedDistant19
Target Audiences: ‘Private Investors’ and or/ ‘Public or private funding
Software is available as well as standard data test on which systems have been trained and tested.
