Goals

Connect the global SCI community working at the intersection of SCI, data science, and AI.

Advance innovation in prediction, prevention, and personalized care through collaborative data projects.

Map the global landscape of SCI datasets to make information findable, accessible, interoperable, reusable (FAIR).

Promote the use of standardized clinical outcome measures and assessments to ensure high-quality, comparable data for research and care improvement.

Educate clinicians, researchers, and students in data-driven methods and ethical AI applications.

Education & Resources: Accessible courses, webinars, and case-based modules on machine learning in SCI care.

Clinical Outcomes & Assessments: Guidance, tools, and training to integrate validated outcome measures into research and care workflows.

Global SCI Dataset Framework: Dynamic map of existing SCI datasets worldwide.

Collaboration & Networking: Connecting SCI professionals, researchers, and innovators.

Innovation & Best Practices: Championing ethical AI and trustworthy data use in SCI.