Artificial intelligence (AI) is rapidly changing all aspects of health, from research to patient care. While many AI training opportunities are available online and in-person, most are short-term or focused on a single field. This isolation means training often occurs in silos defined by health discipline or career field such as computer science or medicine. AI in health works best when people from different backgrounds learn and work together. According to a report by the U.S. House of Representatives Bipartisan House AI Task Force, there is a need for AI training programs that foster interdisciplinary learning, bring experts together across fields, and use multiple teaching approaches to promote lasting understanding.  

With funding from the NIH Common Fund Bridge to Artificial Intelligence (Bridge2AI) program, researchers from the Artificial Intelligence-Ready and Exploratory Atlas for Diabetes Insights (AI-READI) project team sought to address this training gap by developing a collaborative bootcamp that combines core computational training with real-world health care applications, AI-READI Bootcamp. The AI-READI Bootcamp is a short, hands-on training program that introduces AI to trainees from multiple different fields, including public health, science, engineering, and medicine. The program includes a two-week in-person AI/ML bootcamp and a year-long mentored internship. The coursework (80-hours) provides trainees with a foundational understanding of AI/ML from programming to ethics. The in-person experience helps build an informal peer network, encouraging collaborations beyond the formal program.  

The project team launched the bootcamp as a pilot to test and improve its training materials and teaching approaches. Feedback and survey results from the first year were used to strengthen the program for the second year. The initial groups were small, and the evaluation relied on surveys where participants reported their own experiences, so more research is needed to better understand the program’s full impact. Even so, the AI-READI Bootcamp offers a promising model that could be expanded to support AI training across different health-related fields.

Reference:  Nishihara TW, Kalaw FGP, Engmann A, Motoyoshi A, Mensah-Kane P, Gupta D, Patronilo V, Zangwill LM, Hallaj S, Panahi A, Cottrell GW, Voytek B, de Sa VR, Baxter SL. Fostering Multidisciplinary Collaboration in Artificial Intelligence and Machine Learning Education: Tutorial Based on the AI-READI Bootcamp. JMIR Med Educ. 2025 Dec 29;11:e83154. doi: 10.2196/83154. PMID: 41461109; PMCID: PMC12747659.