Software tools for creating standardized multimodal EHR datasets for advancing ophthalmic research using AI

PROJECT SUMMARY Ophthalmology heavily relies on multimodal electronic health record (EHR) data, such as clinical notes, structured data, and imaging, to diagnose, treat, and monitor patients. However, inconsistencies in documentation and the lack of standardized datasets pose significant challenges to leveraging this data for research and clinical applications. Developing robust AI-driven tools that integrate and standardize multimodal EHR data can transform ophthalmic research and improve patient outcomes. This project focuses on advancing the development of AI models, including natural language processing (NLP) and large language models (LLMs) to address these challenges. Specifically, the project will develop tools to enhance data quality, extract key clinical concepts, and standardize multimodal datasets for ophthalmology research. These tools will support tasks such as predicting disease progression, improving clinical workflow efficiency, and enabling data harmonization for multicenter research.