Ontological attention ensembles for capturing semantic concepts in ICD code prediction from clinical text (D19-62)
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Matus Falis, Maciej Pajak, Aneta Lisowska, Patrick Schrempf, Lucas Deckers, Shadia Mikhael, Sotirios Tsaftaris, Alison O’Neil
| Challenge: | a semantically interpretable system for automated ICD coding of clinical text documents is presented . coding errors may result in unpaid claims and loss of revenue, authors argue . |
| Approach: | They propose a semantically interpretable system for automated ICD coding of clinical text documents. |
| Outcome: | The proposed system improves on the MIMIC-III dataset by 2.7% relative to the previous state of the art. |
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