Papers with marco F1

1 papers
Knowledge Injected Prompt Based Fine-tuning for Multi-label Few-shot ICD Coding (2022.findings-emnlp)

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Challenge: Existing methods for ICD coding are limited due to the high-dimensional space of multi-label assignment and the long-tail challenge.
Approach: They propose a prompt-based fine-tuning technique with label semantics to solve this challenge.
Outcome: The proposed method outperforms state-of-the-art methods on a benchmark dataset of code assignment in 14.5% of cases.

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