sujunhao/RENET2
RENET2: High-Performance Full-text Gene-Disease Relation Extraction with Iterative Training Data Expansion
RENET2 helps biomedical researchers and scientists automatically identify and extract gene-disease associations from large volumes of full-text scientific articles. It takes in full-text articles, such as those from PubMed Central or LitCovid, and outputs a list of identified gene-disease relationships. This is ideal for anyone needing to efficiently uncover connections between genes and diseases across extensive biomedical literature.
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Use this if you need to extract gene-disease associations from entire scientific articles, not just abstracts or single sentences, to build comprehensive knowledge bases or perform literature reviews.
Not ideal if you are looking to extract relationships beyond gene-disease, or if your primary data source is clinical notes or unstructured patient records rather than published articles.
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BSD-3-Clause
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Last pushed
Jan 30, 2022
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