ArticleFrontiers in research metrics and analytics2021
ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents.
Article in Frontiers in research metrics and analytics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed.
- ReactionSeek: LLM-powered literature data mining and knowledge discovery in organic synthesis.Nature communications · 2026Article
- Suitability of large language models for extraction of high-quality chemical reaction dataset from patent literature.Journal of cheminformatics · 2024Article
- EnzChemRED, a rich enzyme chemistry relation extraction dataset.Scientific data · 2024Article
- Asking the right questions for mutagenicity prediction from BioMedical text.NPJ systems biology and applications · 2023Article
- Article
- Chemical identification and indexing in full-text articles: an overview of the NLM-Chem track at BioCreative VII.Database : the journal of biological databases and curation · 2023Article
- Deep learning-based automatic action extraction from structured chemical synthesis procedures.PeerJ. Computer science · 2023Article
- Cascade Processes with Micellar Reaction Media: Recent Advances and Future Directions.Molecules (Basel, Switzerland) · 2022Review
- Identifying Chemical Reactions and Their Associated Attributes in Patents.Frontiers in research metrics and analytics · 2021Article
- From Tokenization to Self-Supervision: Building a High-Performance Information Extraction System for Chemical Reactions in Patents.Frontiers in research metrics and analytics · 2021Article
- Ensemble of Deep Masked Language Models for Effective Named Entity Recognition in Health and Life Science Corpora.Frontiers in research metrics and analytics · 2021Article
Corrections and comments
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Authors and funding
15 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chemical patents represent a valuable source of information about new chemical compounds, which is critical to the drug discovery process. Automated information extraction over chemical patents is, however, a challenging task due to the large volume of existing patents and the complex linguistic properties of chemical patents. The Cheminformatics Elsevier Melbourne University (ChEMU) evaluation lab 2020, part of the Conference and Labs of the Evaluation Forum 2020 (CLEF2020), was introduced to support the development of advanced text mining techniques for chemical patents. The ChEMU 2020 lab proposed two fundamental information extraction tasks focusing on chemical reaction processes described in chemical patents: (1)
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.