Before revision: We propose a novel medical term embedding method named CODER, which stands for mediCal knOwledge embeDded tErm Representation . CODER is designed for medical term normalization by providing close vector representations for  terms that represent the same or similar concepts with multi-language support.
After revision: This paper proposes CODER: contrastive learning on knowledge graphs for cross-lingual medical term representation . CODER is designed for medical term normalization by providing close vector representations for terms that represent the same or similar concepts with multi-language support.