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2022 Year in Review

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Dear colleagues,

2023 is a special year for the AIMI Center—our 5th anniversary! Back in 2018, with the help of the Dean's office and the chairs of Radiology, Pathology, and Medicine, we set out to develop a community of like-minded investigators working on AI in biomedicine. We had several key goals: to establish a reputation for outstanding science, to catalyze interdisciplinary collaborations, to attract extramural funding, to educate and engage the community, and to build infrastructure for AI/machine learning research. We thought the new year would a great time to review our accomplishments over the last 5 years. Here is a summary “by the numbers":

  • We built a community by attracting over 150 affiliated faculty from 20 departments across Stanford and by engaging 20 Associate Scholars and Associate Fellows from academia and industry.
  • We catalyzed outstanding open science by awarding over $2M in grants to Stanford investigators, by mentoring 95 students through our health AI “bootcamps,” and by publicly releasing 18 AI-ready clinical data sets (many with code and AI models).
  • We educated the community by producing an AIMI Symposium that attracts a virtual audience of thousands and by partnering with the Human-Centered AI Institute (HAI) on an AI+Health continuing medical education course that features over 100 Stanford speakers and over 1000 paying registrants. We have also engaged dozens of high school students through our summer internship program.
  • We collaborated with industry by establishing 16 active relationships with health AI industry partners and by spinning off 9 health AI companies from labs of AIMI-affiliated faculty.
  • We advanced health AI policy by partnering with the HAI to disseminate 6 AI health policy briefs and by funding policy projects to clarify tort liability for health AI, to report on the dangers of dual use of health AI technologies, and to develop an AI health policy scholars program.
  • We developed infrastructure by assisting the School of Medicine in making petabyte-scale biomedical data accessible in digital form for machine learning experiments, by developing and acquiring tools for image cohort selection, de-identification, and data labeling, and by creating sample data use agreements and institutional review board (IRB) applications.

It is gratifying to see the incredible interdisciplinary collaborations in AIMI affiliated laboratories, and to see the response our work receives in both the computer science and the clinical research communities. With your continued partnership, we look forward to continued growth in Stanford’s pre-eminence by attracting and supporting outstanding scientists working in AI and biomedicine.

We wish you all a happy and healthy 2023 and look forward to seeing you in person at an AIMI event soon.