Recent Advances, Applications and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2024 Symposium

Adibi, Amin, Cao, Xu, Ji, Zongliang, Kaur, Jivat Neet, Chen, Winston, Healey, Elizabeth, Nuwagira, Brighton, Ye, Wenqian, Woollard, Geoffrey, Xu, Maxwell A, Cui, Hejie, Xi, Johnny, Chang, Trenton, Bikia, Vasiliki, Zhang, Nicole, Noori, Ayush, Xia, Yuan, Hossain, Md. Belal, Frank, Hanna A., Peluso, Alina, Pu, Yuan, Shen, Shannon Zejiang, Wu, John, Fallahpour, Adibvafa, Mahbub, Sazan, Duncan, Ross, Zhang, Yuwei, Cao, Yurui, Xu, Zuheng, Craig, Michael, Krishnan, Rahul G., Beheshti, Rahmatollah, Rehg, James M., Karim, Mohammad Ehsanul, Coffee, Megan, Celi, Leo Anthony, Fries, Jason Alan, Sadatsafavi, Mohsen, Shung, Dennis, McWeeney, Shannon, Dafflon, Jessica, Jabbour, Sarah

arXiv.org Artificial Intelligence 

The fourth Machine Learning for Health (ML4H) symposium was held in person on December 15th and 16th, 2024, in the traditional, ancestral, and unceded territories of the Musqueam, Squamish, and Tsleil-Waututh Nations in Vancouver, British Columbia, Canada. The symposium included research roundtable sessions to foster discussions between participants and senior researchers on timely and relevant topics for the ML4H community. The organization of the research roundtables at the conference involved 13 senior and 27 junior chairs across 13 tables. Each roundtable session included an invited senior chair (with substantial experience in the field), junior chairs (responsible for facilitating the discussion), and attendees from diverse backgrounds with an interest in the session's topic.

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