AI4Function: A New Interdisciplinary Community Bart Desmet 0 3 Hongfang Liu 0 2 Junichi Tsujiig 0 Denis Newman-Grifis Johns Hopkins University , Baltimore, Maryland , USA Mayo Clinic , Rochester, Minnesota , USA National Institutes of Health Clinical Center , Bethesda, Maryland , USA Stanford University , Stanford, California , USA University of Minnesota , Minneapolis, Minnesota , USA University of Pittsburgh , Pittsburgh, Pennsylvania , USA

a Artificial intelligence (AI) technologies are increasingly applied to drive innovation and improve care in diverse areas of medicine. In recent years, new areas of research have emerged at the intersection of AI technologies and the measurement and optimization of functional outcomes, with developments such as: (1) the use of wearable sensors to capture physical function; (2) natural language processing to analyze clinical observations of function; and (3) the development of AI-driven assistive technologies. These innovations have largely developed independently of one another, without the benefit of a common venue for researchers to share insights and exchange ideas about AI for function across disciplinary boundaries.

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dnewmangrifis@pitt.edu

(D. Newman-Grifis)

The workshop was held on January 7th and 8th, 2021. In addition to the papers included in these proceedings, the program included: • Presentation of two abstracts: “Challenges of developing a natural language processing method with electronic health records to identify persons with chronic mobility disability,” by Nicole Agaronnik, Charlotta Lindvall, Areej El-Jawahri, Wei He, and Lisa Iezzoni; and “Building a Mobility Dictionary for Whole-Person Functional Assessment,” by Ayah Zirikly, Bart Desmet, Denis Newman-Grifis, Pei-Shu Ho, Jonathan Camacho Maldonado, Maryanne Sacco, and Julia Porcino. • A keynote presentation from Dr. Hongfang Liu (Mayo Clinic). • A panel discussion regarding next steps and future directions for AI research in function, disability, and health.

Program Committee The organizers of AI4Function 2020 wish to thank the program committee members for their hard work in ensuring a diverse and high-quality program through their thoughtful reviews. We are also grateful to our panel members for their engaging contributions to the workshop. Finally, we would like to thank the organizers of IJCAI-PRICAI 2020 for hosting the workshop. The workshop was supported in part by the Intramural Research Program of the National Institutes of Health and the U.S. Social Security Administration.