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2019 EMNLP EMNLP 2019

MedCATTrainer: A Biomedical Free Text Annotation Interface with Active Learning and Research Use Case Specific Customisation

Abstract

AbstractAn interface for building, improving and customising a given Named Entity Recognition and Linking (NER+L) model for biomedical domain text, and the efficient collation of accurate research use case specific training data and subsequent model training. Screencast demo available here: https://www.youtube.com/watch?v=lM914DQjvSo

🌉 Interdisciplinary Bridge — Artificial Intelligence and Healthcare & Medicine and Machine Learning and Natural Language Processing
🐣 Hot Topic Early Bird — model training
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Thomas Searle , Zeljko Kraljevic , Rebecca Bendayan , Daniel Bean , Richard Dobson

Topics

Artificial Intelligence > Learning Paradigms > Transfer Learning Machine Learning > Learning Types > Active Learning Healthcare & Medicine > Clinical > Clinical NLP Natural Language Processing > Applications > Named Entity Recognition Machine Learning > Learning Paradigms > Active Learning

Keywords

active learning entity linking named entity recognition model training biomedical text clinical nlp annotation interface
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