Fostering Multidisciplinary Collaboration in Artificial Intelligence and Machine Learning Education: Tutorial Based on the AI-READI Bootcamp
The AI-READI Bootcamp illustrates how feedback-driven, multidisciplinary training embedded within a longitudinal mentored research program can bridge technical and clinical expertise in biomedical AI. Core elements-diverse trainee cohorts, applied learning with biomedical datasets, and sustained mentorship-offer a replicable model for preparing health professionals for the evolving AI/ML landscape. Future iterations will incorporate additional prebootcamp onboarding modules, objective skill assessments, and long-term tracking of research engagement and productivity.
Authors
- Garrison W. Cottrell (ORCID: https://orcid.org/0000-0001-7538-1715)
- Deepa Gupta (ORCID: https://orcid.org/0000-0002-5524-6898)
- Taiki W Nishihara (ORCID: https://orcid.org/0000-0002-1081-6180)
- Bradley Voytek (ORCID: https://orcid.org/0000-0003-1640-2525)
- Fritz Gerald P. Kalaw (ORCID: https://orcid.org/0000-0002-3940-2272)
- Linda M. Zangwill (ORCID: https://orcid.org/0000-0002-1143-5224)
- Amirhossein Panahi (ORCID: https://orcid.org/0000-0002-4624-1219)
- Sally L. Baxter (ORCID: https://orcid.org/0000-0002-5271-7690)
- Virginia R. de (ORCID: https://orcid.org/0000-0002-0989-3576)
- Shahin Hallaj (ORCID: https://orcid.org/0000-0002-9541-1915)
- Victoria Patronilo (ORCID: https://orcid.org/0000-0002-3504-6514)
- Aya Motoyoshi
- Adelle Engmann (ORCID: https://orcid.org/0009-0006-1015-2712)
- Paapa Mensah-Kane
Institutions
- Fleet Science Center (US)
- University of Washington (US)
- University of California San Diego (US)
- South University (US)
- Stanford University (US)
Publication Details
- Journal
- JMIR Medical Education
- Published
- 2025-11-10
- DOI
- https://doi.org/10.2196/83154
- Citations
- 1
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.65