BRIDGE2AI

AI/ML for Clinical Care

AI/ML for Clinical Care

Patient-Focused Collaborative Hospital Repository Uniting Standards (CHoRUS) for Equitable AI

The goal of the AI/ML for Clinical Care Network is to develop the most diverse, high-resolution, ethically sourced, AI-ready data set to answer the grand challenge of improving recovery from acute illness.

  • This collaboration spans 20 academic centers, of which 14 will contribute as Data Acquisition centers.
  • Patient-focused efforts will determine the ethical and legal approaches to manage privacy and bias, while accounting for Social Determinants of Health.
  • Unified standards will harmonize multi-modal EHR, waveform, imaging, and text data.
  • A visualization and annotation environment will label data with targets important for prediction.
  • A comprehensive set of approaches will develop the skills and workforce for a next generation of diverse academic and community AI scientists.
  • Federated access will enable sampling methods to ensure a balanced and diverse cohort.
  • Collaborating with Bridge2AI and 3 other data generation projects, the AI/ML for Clinical Care Network will help us cross the Bridge2AI network together.

chorus4ai.org

Who We Are

Paul Vespa

Co-Investigator
University of California Los Angeles

Michael Young

Co-Investigator
Massachusetts General Hospital