Feasibility of cross-vendor linkage of ophthalmic images with electronic health record data: an analysis from the IRIS Registry ® .
Michael MbagwuZhongdi ChuDurga BorkarAlex KoshtaNisarg ShahAracelis Z TorresHylton KalvariaFlora LumTheodore LengPublished in: JAMIA open (2024)
Using identifiers from DICOM metadata, we created an automated pipeline to connect longitudinal real-world clinical data comprehensively and accurately to various imaging modalities from multiple manufacturers at the patient and visit levels. The process has produced an enriched and multimodal IRIS Registry, bridging the gap between basic research and clinical care by enabling future applications in artificial intelligence algorithmic development requiring large linked clinicoimaging datasets.
Keyphrases
- electronic health record
- artificial intelligence
- big data
- deep learning
- machine learning
- clinical decision support
- healthcare
- pain management
- adverse drug
- palliative care
- convolutional neural network
- gene expression
- chronic pain
- quality improvement
- optical coherence tomography
- photodynamic therapy
- hepatitis c virus
- hiv testing