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arXiv Machine Learning By Mohammad Mansoori, Amira Soliman, Farzaneh Etminani

LTR-ICD: A Ranking-Aware Framework for Automatic ICD Coding

Read the original on arXiv Machine Learning →

The paper introduces LTR-ICD, a ranking‑aware framework that treats automatic ICD coding as a combined classification and ranking problem rather than a pure classification task. By incorporating the order of diagnostic codes, the method improves the identification of high‑priority codes, achieving a 47% accuracy in correctly ranking primary diagnoses versus 20% for existing classifiers. The model also outperforms prior work on micro‑ and macro‑F1 scores, reaching 0.6065 and 0.2904 respectively.

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 Machine Learning.

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