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Article Abstract
Context: We present a post-hoc approach to improve the recall of ICD classification.
Method: The proposed method can use any classifier as a backbone and aims to calibrate the number of codes returned per document. We test our approach on a new stratified split of the MIMIC-III dataset.
Results: When returning 18 codes on average per document we obtain a recall that is 20% better than a classic classification approach.
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| http://dx.doi.org/10.3233/SHTI230264 | DOI Listing |
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