DGP/GC Collaborations

The NIH Bridge2AI Consortium is presently engaging with 4 unique AI/ML BioMed data generation efforts dubbed Grand Challenges.

• Precision Public Health Grand Challenge (Voice)
• Salutogenesis Grand Challenge (AI-READI)
• Clinical Care Grand Challenge (CHoRUS)
• Functional Genomics Grand Challenge (CM4AI)

The Bridge2AI Training Working Group is a collaborative effort between the Bridge Center and each Grand Challenge (GC). We work together to provide resources for data users to learn about datasets, standards, analysis tools, and potential research opportunities unique to each respective GC within the Bridge2AI Consortium. We currently offer the following curriculum learning opportunities:

• [Voice AI Training Resource]: Voice AI Summer School, Voice AI Webinar Series.
• [CHoRUS Training Resource]: The 2024 AI for Clinical Care Workshop.
• [CM4AI Training Resource]: CM4AI Product Documentation, CM4AI Tools & Resources. 
• [AI-READI Training Resource]: AI-READI Yearlong Research Internship Program (August 2024 – July 2025).

Each Bridge2AI GC engages with datasets unique to their respective objectives and serves the rapidly growing community of scholars interested in AI/ML BioMed applications by sharing lessons learned and guiding future AI/ML BioMed scholars through lectures. Below are lectures developed by the Bridge2AI Training Working Group introducing Bridge2AI Scholars to respective Grand Challenge datasets providing scholars with the technical know-how needed to get started on their own AI/ML BioMed research investigations.

Specific to each GC, lectures in this curriculum:

• Provide clinical context for data collection;
• Characterize the features of each data types;
• Describe how the data was collected (meta data);
• Enumerate existing data standards, APIs, and tools;
• Discuss case studies & potential applications;