Papers by Ferdinand Schlatt

1 papers
Mining Health-related Cause-Effect Statements with High Precision at Large Scale (2022.coling-1)

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Challenge: Existing methods for assessing the health relatedness of phrases and sentences are slower and less effective than state-of-the-art medical entity linkers.
Approach: They propose a termhood score that achieves 69% recall at over 90% precision on a web dataset with cause-effect statements.
Outcome: The proposed method achieves 69% recall at over 90% precision on a web dataset with cause-effect statements.

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