EDIT AI

The Emerging Diagnostic and Investigative Technologies (EDIT) AI program is a national, cancer-focused internship hosted by Dartmouth Health and the Dartmouth Cancer Center’s CRTEC initiative, as well as Cedars Sinai Medical Center, founded in the Departments of Pathology and Laboratory Medicine. Launched in 2019, EDIT AI prepares the next generation of biomedical investigators by immersing high school students in authentic research at the intersection of artificial intelligence (AI) and cancer medicine. Its fully remote, multi-institutional model—including a Virtual Student Laboratory, structured preparatory workshops, tiered mentorship, and a national seminar series—mirrors modern biomedical research and attracts a diverse, high-density talent pool unconstrained by geography.

Since inception, EDIT AI has engaged nearly 300 students from 25 states, scaling from an initial cohort of 6 to nearly 90 participants annually. Outcomes demonstrate both feasibility and impact:

• Academic Advancement: Alumni consistently pursue higher education at leading colleges and universities, with many continuing in STEM and pre-medical pathways.
• Scholarly Contributions: More than 30 students have authored peer-reviewed manuscripts, contributing to 39 publications, alongside dozens of national and international conference presentations.
• Leadership Development: Through a three-track progression model (Skills, Advanced, Mentor), students advance from foundational programming skills to mentored research to near-peer leadership roles.
• National Recognition: Participants have presented at forums such as AACR and ML4Health, showcasing their ability to bridge computational and clinical perspectives.
• Scholarship & Career Impact: Many alumni have secured competitive scholarships and remain engaged as mentors and collaborators, sustaining the program’s long-term value.

Students in the EDIT AI program have opportunities to spearhead multiple projects while interfacing directly with clinicians and will be exposed to a blend of interdisciplinary research perspectives.