Bridge2AI: Building A Cross-disciplinary Curriculum Towards AI-Enhanced Biomedical and Clinical Care
Year: 2025
Type: preprint
Abstract: Objective: As AI becomes increasingly central to healthcare, there is a pressing need for bioinformatics and biomedical training systems that are personalized and adaptable. Materials and Methods: The NIH Bridge2AI Training, Recruitment, and Mentoring (TRM) Working Group developed a cross-disciplinary curriculum grounded in collaborative innovation, ethical data stewardship, and professional development within an adapted Learning Health System (LHS) framework. Results: The curriculum integrates foundational AI modules, real-world projects, and a structured mentee-mentor network spanning Bridge2AI Grand Challenges and the Bridge Center. Guided by six learner personas, the program tailors educational pathways to individual needs while supporting scalability. Discussion: Iterative refinement driven by continuous feedback ensures that content remains responsive to learner progress and emerging trends. Conclusion: With over 30 scholars and 100 mentors engaged across North America, the TRM model demonstrates how adaptive, persona-informed training can build interdisciplinary competencies and foster an integrative, ethically grounded AI education in biomedical contexts.
Source: arXiv (Cornell University)
Authors: Rincon, John, Pelletier, Alexander R., Gilliland, Destiny, Wang, Wei, Wang, Ding, Sankar, Baradwaj S., Scott-Sheldon, Lori, Gebreab, Samson, Hersh, William, Rashidi, Parisa, Baxter, Sally, Schulz, Wade, Ideker, Trey, Bensoussan, Yael, Boutros, Paul C., Bui, Alex A. T., Walsh, Colin, Watson, Karol E., Ping, Peipei
Language: English
Subfield: Health Informatics
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4415320233
Cites:
Cited by:
Related to: