On embedding-based automatic mapping of clinical classification system: handling linguistic variations and granular inconsistencies

Our findings demonstrate that integrating the representational power of pretrained encoders with LLM reasoning offers a robust, scalable strategy for automatic ICD mapping.

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Publication Details

Journal
Journal of the American Medical Informatics Association
Published
2026-01-12
DOI
https://doi.org/10.1093/jamia/ocag004
Primary Topic
Machine Learning in Healthcare
Type
article
Field-Weighted Citation Impact
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article

On embedding-based automatic mapping of clinical classification system: handling linguistic variations and granular inconsistencies

Oliver Obst, Jeewani Anupama Ginige, Santosh Purja Pun, Jim Basilakis
Journal of the American Medical Informatics Association
Machine Learning in Healthcare
article

On embedding-based automatic mapping of clinical classification system: handling linguistic variations and granular inconsistencies

Oliver Obst, Jeewani Anupama Ginige, Santosh Purja Pun, Jim Basilakis
article en

Abstract

Our findings demonstrate that integrating the representational power of pretrained encoders with LLM reasoning offers a robust, scalable strategy for automatic ICD mapping.

Journal of the American Medical Informatics Association
Western Sydney University (AU)
Openalex Percentile: Top 73%
Machine Learning in Healthcare
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