Papers by Zeljko Kraljevic
MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation (D19-3)
Copied to clipboard
| Challenge: | 80% of biomedical data is stored in unstructured text such as electronic health records (EHRs). |
| Approach: | They propose a web-based interface for building, improving and customising a given Named Entity Recognition and Linking (NER+L) model for biomedical domain text. |
| Outcome: | The proposed interface is designed to build, improve and customise a NER+L model for biomedical domain text and collate accurate research use case specific training data. |