som-shahlab/trove
Weakly supervised medical named entity classification
Trove helps medical researchers and healthcare analysts quickly identify specific medical entities like symptoms or conditions within large volumes of medical texts such as electronic health records or scientific papers. It takes medical text and publicly available medical ontologies (like UMLS) to automatically extract and classify these entities, without requiring manual labeling of training data. This is ideal for those needing to analyze clinical narratives at scale.
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Use this if you need to extract and classify medical terms from clinical text, social media, or scientific literature efficiently, especially when privacy concerns make manual data labeling difficult.
Not ideal if you need high-precision classification for domains outside of biomedical and healthcare, or if you prefer to manually label all your training data.
Stars
73
Forks
21
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 23, 2022
Commits (30d)
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