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Biomedical science is in the midst of a technological revolution driven by innovations in deep learning neural network architecture and availability of computational power. Cutting-edge AI-based techniques are being applied to every sub-field of the biological sciences to produce novel, ground-breaking advancements.
The Artificial Intelligence Interest Group (AIIG) aims to promote the awareness, understanding, and adoption of Artificial Intelligence and Deep Learning approaches across the NIH. We aim to take a broad view of AI/DL across all fields in the biomedical sciences, with the idea that learning about many different applications of this technology will yield a deeper understanding of how it works and facilitate cross-pollination between field. The group is intended for both experts and novices: We believe that everyone can find value in learning about and discussing a wide range of topics in this burgeoning field.
Regular meetings are in the form of a weekly AI Journal Club and Seminar Series, where AIIG members from various scientific backgrounds take turns leading a session on a topic of interest. We help organize a new yearly event, the NIH Artificial Intelligence Symposium, where researchers across NIH can gather to learn and share their AI-related research. We will also promote other Artificial Intelligence and Deep Learning-related events to the listserv .
Contact Ryan O'Neill (ryan.o'neill@nih.gov) for more information.
Note: This AIIG reformed in 2024 and was previously called the Deep Learning & AI in Biomedical Sciences Interest Group. Prior to 2024, the AIIG was led by June Lee, M.D., Ph.D., LeeJun@mail.nih.gov .
nasser.rusan@nih.gov NHLBI Nasser Rusan, Ph.D. https://irp.nih.gov/pi/nasser-rusan brb@mail.nih.gov Bernard Brooks, Ph.D. https://irp.nih.gov/pi/bernard-brooks Scientific Interest Groups Ryan O’Neill, Ph.D. fnu.samarjeet@nih.gov Samar Samarjeet, Ph.D. https://list.nih.gov/cgi-bin/wa.exe?A0=ARTIFICIAL-INTELLIGENCE