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2022 EMNLP EMNLP 2022

Biomedical NER for the Enterprise with Distillated BERN2 and the Kazu Framework

Abstract

AbstractIn order to assist the drug discovery/development process, pharmaceutical companies often apply biomedical NER and linking techniques over internal and public corpora. Decades of study of the field of BioNLP has produced a plethora of algorithms, systems and datasets. However, our experience has been that no single open source system meets all the requirements of a modern pharmaceutical company. In this work, we describe these requirements according to our experience of the industry, and present Kazu, a highly extensible, scalable open source framework designed to support BioNLP for the pharmaceutical sector. Kazu is a built around a computationally efficient version of the BERN2 NER model (TinyBERN2), and subsequently wraps several other BioNLP technologies into one coherent system.

🌉 Interdisciplinary Bridge — Deep Learning and Healthcare & Medicine and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — enterprise nlp
🐣 Hot Topic Early Bird — drug discovery
🐝 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

Wonjin Yoon , Richard Jackson , Elliot Ford , Vladimir Poroshin , Jaewoo Kang

Topics

Machine Learning > Application Areas > Knowledge Distillation Deep Learning > Techniques > Pretraining Healthcare & Medicine > Research > Bioinformatics Natural Language Processing > Applications > Named Entity Recognition Machine Learning > Learning Types > Knowledge Distillation Deep Learning > Learning Types > Knowledge Distillation

Keywords

text mining knowledge distillation entity linking information extraction named entity recognition drug discovery biomedical named entity recognition biomedical text mining named entity linking scalable framework enterprise nlp computationally efficient
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