Multimodal Data Fusion Integrating Text and Medical Imaging Data in Electronic Health Records

This research presents a technique for integrating textual and medical imaging data into EHRs. Potential benefits of the seamless integration of diverse healthcare data sets include improved diagnostic precision, enhanced treatment efficacy, and accelerated medical research. By utilizing state-of-the-art algorithms and techniques, the proposed method integrates textual and imaging data in a complementary fashion to generate a comprehensive picture of patients’ health profiles. A comprehensive study validates the beneficial impacts of the approach on data interoperability and CDA in a broader sense. By incorporating narrative data and imaging findings, electronic health records (EHRs) enable personalized treatment and precision medicine by comprehensively assessing a patient’s condition. By presenting a comprehensive solution that surpasses current capabilities, this study makes a valuable contribution to the ever-evolving field of healthcare informatics. It paves the way for a more streamlined and effective healthcare system.