Practical Guides to Healthcare AI Data
Explore how different healthcare data modalities are structured, prepared and used in AI development and evaluation.
Understand healthcare data by modality
These guide areas help teams think through formats, metadata, annotation requirements and quality considerations.
Medical Imaging
DICOM, X-ray, CT, MRI, ultrasound, dental imaging and imaging AI workflows.
Digital Pathology
Whole-slide images, pathology labels, tissue structures and computational pathology data.
Physiological Signals
ECG, EEG, PPG, SpO2, wearables, sleep and remote-monitoring signals.
Clinical Text & NLP
Clinical notes, EHR data, structured records and healthcare language-model data.
Medical Audio & Video
Clinical conversations, procedures, surgery, endoscopy and temporal annotation.
Biomedical Data
Genomics, pharmaceuticals, clinical trials, laboratory and research datasets.
Need a healthcare dataset for your AI project?
Browse available dataset categories or discuss a custom sourcing requirement.