2021
EMNLP
EMNLP 2021
Coreference Resolution for the Biomedical Domain: A Survey
Abstract
AbstractIssues with coreference resolution are one of the most frequently mentioned challenges for information extraction from the biomedical literature. Thus, the biomedical genre has long been the second most researched genre for coreference resolution after the news domain, and the subject of a great deal of research for NLP in general. In recent years this interest has grown enormously leading to the development of a number of substantial datasets, of domain-specific contextual language models, and of several architectures. In this paper we review the state of-the-art of coreference in the biomedical domain with a particular attention on these most recent developments.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Healthcare & Medicine and Natural Language Processing
🐝
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
Topics
Natural Language Processing > Understanding > Coreference Resolution
Healthcare & Medicine > Clinical > Clinical NLP
Healthcare & Medicine > Research > Bioinformatics
Artificial Intelligence > Core AI > Natural Language Processing
Healthcare & Medicine > Clinical > Medical NLP
Natural Language Processing > Applications > Coreference Resolution