Enhancing ophthalmology medical record management with multi-modal knowledge graphs.

ABSTRACT: The electronic medical record management system plays a crucial role in clinical practice, optimizing the recording and management of healthcare data. To enhance the functionality of the medical record management system, this paper develops a customized schema designed for ophthalmic diseases. A multi-modal knowledge graph is constructed, which is built upon expert-reviewed and de-identified real-world ophthalmology medical data. Based on this data, we propose an auxiliary diagnostic model based on a contrastive graph attention network (CGAT-ADM), which uses the patient's diagnostic results as anchor points and achieves auxiliary medical record diagnosis services through graph clustering. By implementing contrastive methods and feature fusion of node types, text, and numerical information

SUBMITTER: Gao W 

PROVIDER: S-EPMC11455959 | biostudies-literature | 2024 Oct

REPOSITORIES: biostudies-literature