Fine-tuned e5_large LLM reaches 0.866 F1_micro on ICD classification of 145k Spanish psychiatric texts, outperforming BoW, TF-IDF, and other transformers.
Surpassing GPT- 4 medical coding with a two-stage approach
2 Pith papers cite this work. Polarity classification is still indexing.
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Adding ICD-9 data to ICD-10 training boosts micro F1 by 27% on 18K rare codes and improves macro metrics on frequent codes in a label-wise attention model.
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Automated ICD Classification of Psychiatric Diagnoses: From Classical NLP to Large Language Models
Fine-tuned e5_large LLM reaches 0.866 F1_micro on ICD classification of 145k Spanish psychiatric texts, outperforming BoW, TF-IDF, and other transformers.
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Bridging the Version Gap: Multi-version Training Improves ICD Code Prediction, Especially for Rare Codes
Adding ICD-9 data to ICD-10 training boosts micro F1 by 27% on 18K rare codes and improves macro metrics on frequent codes in a label-wise attention model.