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Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium

Authors :
Jeong, Hyewon
Jabbour, Sarah
Yang, Yuzhe
Thapta, Rahul
Mozannar, Hussein
Han, William Jongwon
Mehandru, Nikita
Wornow, Michael
Lialin, Vladislav
Liu, Xin
Lozano, Alejandro
Zhu, Jiacheng
Kocielnik, Rafal Dariusz
Harrigian, Keith
Zhang, Haoran
Lee, Edward
Vukadinovic, Milos
Balagopalan, Aparna
Jeanselme, Vincent
Matton, Katherine
Demirel, Ilker
Fries, Jason
Rashidi, Parisa
Beaulieu-Jones, Brett
Xu, Xuhai Orson
McDermott, Matthew
Naumann, Tristan
Agrawal, Monica
Zitnik, Marinka
Ustun, Berk
Choi, Edward
Yeom, Kristen
Gursoy, Gamze
Ghassemi, Marzyeh
Pierson, Emma
Chen, George
Kanjilal, Sanjat
Oberst, Michael
Zhang, Linying
Singh, Harvineet
Hartvigsen, Tom
Zhou, Helen
Okolo, Chinasa T.
Publication Year :
2024

Abstract

The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between participants and senior researchers on timely and relevant topics for the \ac{ML4H} community. Encouraged by the successful virtual roundtables in the previous year, we organized eleven in-person roundtables and four virtual roundtables at ML4H 2022. The organization of the research roundtables at the conference involved 17 Senior Chairs and 19 Junior Chairs across 11 tables. Each roundtable session included invited senior chairs (with substantial experience in the field), junior chairs (responsible for facilitating the discussion), and attendees from diverse backgrounds with interest in the session's topic. Herein we detail the organization process and compile takeaways from these roundtable discussions, including recent advances, applications, and open challenges for each topic. We conclude with a summary and lessons learned across all roundtables. This document serves as a comprehensive review paper, summarizing the recent advancements in machine learning for healthcare as contributed by foremost researchers in the field.<br />Comment: ML4H 2023, Research Roundtables

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2403.01628
Document Type :
Working Paper