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arXiv AI By Xu Zhang, Wenxin Ma, Chenxu Wu, Rongsheng Wang, Zhiyang He, Xiaodong Tao, Kun Zhang, S. Kevin Zhou

From Documents to Spans: Span-Centric Learning for LLM-based Explainable Medical Coding

Read the original on arXiv AI →

The paper introduces Span-Centric Learning (SCL), a method that decouples coding knowledge acquisition from its application in full clinical documents. SCL first trains on short text spans to learn coding knowledge, then fine‑tunes on a small set of annotated documents, enabling an 8B LLM to outperform state‑of‑the‑art methods with only 248 full documents. The approach also yields explicit, human‑aligned supporting evidence for each predicted ICD code and can learn code knowledge from spans even when the codes are absent from the full documents.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

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