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

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