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Automated knowledge curation for biomedical ontologies is key to ensure that they remain comprehensive, high-quality and up-to-date.
Nltk: the natural language toolkit
Steven Bird · 2006
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Chebi: a database and ontology for chemical entities of biological interest
Kirill Degtyarenko, Paula De Matos, Marcus Ennis, Janna Hastings, Martin Zbinden, Alan McNaught, Rafael Alcántara, Michael Darsow, Mickaël Guedj, and Michael Ashburner · 2007
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Chemical entities of biological interest: an update
Paula De Matos, Rafael Alcántara, Adriano Dekker, Marcus Ennis, Janna Hastings, Kenneth Haug, Inmaculada Spiteri, Steve Turner, and Christoph Steinbeck · 2010
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Efficient Estimation of Word Representations in Vector Space
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Optimal threshold determination for interpreting semantic similarity and particularity: application to the comparison of gene sets and metabolic pathways using go and chebi
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Link Prediction on a Network of Co-occurring MeSH Terms: Towards Literature-based Discovery
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Big data application in biomedical research and health care: a literature review
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Daniel M Bean, Honghan Wu, Ehtesham Iqbal, Olubanke Dzahini, Zina M Ibrahim, Matthew Broadbent, Robert Stewart, and Richard JB Dobson · 2017
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Deep reinforcement learning from human preferences
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Mapping text to knowledge graph entities using multi-sense LSTMs
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, Ilya Sutskever, et al · 2018
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Knowledge graphs
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Yingtong Liu, Junguk Hur, Wallace KB Chan, Zhigang Wang, Jiangan Xie, Duxin Sun, Samuel Handelman, Jonathan Sexton, Hong Yu, and Yongqun He · 2021
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A survey on clinical natural language processing in the united kingdom from 2007 to 2022
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