UniMedAbstractor (UMA) leverages frontier language models to automatically extract structured medical information from unstructured clinical notes without manual annotation or rule-crafting.

• Zero-shot capabilities enable extraction of patient data across various medical attributes
• Specialized for oncology with focus on performance status, treatments, tumor details, and TNM staging
• Scales efficiently by eliminating traditional manual abstraction efforts
• Evaluated on real-world patient data demonstrating practical clinical application

This breakthrough matters because it addresses the critical challenge that most patient information exists in unstructured text, making structured data extraction traditionally labor-intensive and difficult to scale.

Universal Abstraction: Harnessing Frontier Models to Structure Real-World Data at Scale