Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2022 Symposium

作者：Stefan Hegselmann, Helen Zhou, Yuyin Zhou, Jennifer Chien, Sujay Nagaraj, Neha Hulkund, Shreyas Bhave, Michael D. Oberst, Amruta Pai, Caleb N. Ellington, Wisdom Ikezogwo, Jason Dou, Monica Agrawal, Changye Li, Peniel Argaw, Arpita Biswas, Mehak Gupta, Xinhui Li, Marta Lemanczyk, Yuhui Zhang, Christian Garbin, Elizabeth Healey, Heejong Kim, Claire Boone, Roxana Daneshjou, Siyu Shi, Nicola Pezzotti, Stephen Pfohl, Edwin Fong, Aakanksha Naik, Ben Lengerich, Ying Xu, Jonathan Bidwell, Mark Sendak, Bitgoeul Kim, Nathaniel Hendrix, Dimitris Spathis, Jun Seita, Bastiaan Quast, Megan Coffee, Collin Stultz, Irene Y. Chen, Shalmali Joshi, Girmaw Abebe Tadesse · 发表于：Zenodo (CERN European Organization for Nuclear Research) · 年份：2023 · DOI：10.5281/zenodo.7951122 · 研究领域：Artificial Intelligence in Healthcare、Machine Learning in Healthcare

The second Machine Learning for Health (ML4H) symposium was held both virtually and in-person on November 28, 2022, in New Orleans, Louisiana, USA (Parziale et al., 2022). The symposium included research roundtable sessions to foster discussions between participants and senior researchers on timely and relevant topics for the ML4H community. Encouraged by the successful virtual roundtables in the previous year (Roy et al., 2021), we organized nine in-person and four virtual roundtables at ML4H 2022 (Parziale et al., 2022). A roundtable session included invited senior chairs (with substantial experience in the field), junior chairs (responsible for facilitating the discussion), and attendees from di- verse backgrounds with interest in the session’s topic. This document explains the organization process we used and compiles the takeaways from the roundtable discussions, including recent advances, applications, and open challenges for each topic. We conclude with a summary and lessons learned across all roundtables.