The Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI project is creating a diverse, ethically sourced, AI-ready dataset to advance recovery from acute illness. This flagship effort aims to capture the complexity of real-world clinical care through multimodal data—including EHRs, imaging, waveforms, and clinical text—harmonized using unified standards.

A collaboration among 20 academic institutions (with 14 serving as Data Acquisition Centers), CHoRUS emphasizes a patient-focused approach, addressing privacy, bias, and Social Determinants of Health. A custom environment will support the annotation of clinically meaningful outcomes, enabling predictive modeling and responsible AI development.

The project also includes dedicated training efforts to build a skilled, diverse AI/ML workforce. Through federated access and balanced sampling, CHoRUS will contribute to a strong foundation for future biomedical AI research.