Longitudinal Medical Data | Global Coverage

This dataset provides 2–3 years of longitudinal, patient-level clinical data, enabling users to follow the progression of care over time rather than analyze isolated encounters. Each patient record can include laboratory test results, medical imaging studies with associated DICOM files and radiology reports, medications administered during care, documented diagnoses, and discharge summaries or forms. The longitudinal structure allows researchers and AI developers to examine how clinical findings, treatments, imaging results, and outcomes evolve across multiple visits and episodes of care. This makes the dataset suitable for applications such as disease-progression modeling, treatment-response analysis, clinical outcome prediction, real-world evidence generation, patient stratification, multimodal AI development, and retrospective observational research. Where available, data can be linked across modalities to provide a more complete view of the patient journey, combining structured clinical variables with unstructured reports and imaging data. The dataset is de-identified and prepared for research, analytics, and machine-learning use in accordance with applicable privacy and data-protection requirements.