J. Rokne

MMAC-Net: A Multi-Modal Multi-Label Attention-Based Deep Learning Approach for Automated ICD-9 Coding of Rare Disease Admissions from Electronic Health Records

A multi-modal deep learning framework designed to enhance the retrospective assignment of ICD-9 codes to admissions involving rare pathologies, and underscores that incorporating structured clinical context partially mitigates the limitations of purely natural language processing approaches.