MIMIC-CXR-Ext-MIMIC-CXR-DB: Linking MIMIC-IV Chest Radiographs with Rich and Harmonized Clinical Context
Year: 2026
Type: dataset
Abstract: MIMIC-CXR-DB is a relational clinical database comprising 146,333 chest radiographs linked to hospital admissions, designed to support research at the intersection of electronic health records (EHRs) and chest radiography. The database integrates hospital admissions data, demographic characteristics, diagnoses, laboratory measurements, radiology metadata, radiographic findings, and discharge documentation. It is derived primarily from MIMIC-IV and MIMIC- CXR-JPG, enabling admission-level and imaging-based multimodal analyses. Radiographic findings are derived from chest X-ray reports in the MIMIC-CXR- JPG dataset and include standardized indicators of common thoracic conditions such as atelectasis, cardiomegaly, consolidation, edema, pneumonia, pneumothorax, and pleural abnormalities, alongside detailed DICOM-derived imaging metadata. Laboratory data are normalized using dictionary tables to enable consistent interpretation of test results across admissions. Clinical findings from free-text radiology and discharge reports are extracted as triples using Named Entity Recognition and Ontology-Based Entity Linking and represented in two dedicated tables to improve the discoverability of clinical insights. All data are de-identified and derived from the MIMIC ecosystem under established privacy and data-access requirements. By providing admission-level linkage between clinical variables and imaging studies, MIMIC- CXR-DB enables reproducible research in clinical epidemiology, radiology, and machine learning, particularly for the development and evaluation of models that combine electronic health records with medical imaging.
Source: PhysioNet
DOI: 10.13026/pmv9-jd43
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7215106916
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