ACM Conference Showcases Research at the Intersection of Healthcare and Machine Learning

Interdisciplinary CHIL Conference Brings Together Clinicians and Computing Professionals to Address Challenges and Opportunities

New York, NY, March 30, 2021 – The Association for Computing Machinery Conference on Health, Inference, and Learning (ACM CHIL 2021), being held virtually from April 8-9, brings together a cross-disciplinary representation of clinicians and researchers from industry and academia in machine learning, health policy, causality, fairness, and other related areas.

ACM CHIL provides a forum for research that in many cases seeks to move advanced computing technologies, such as machine learning and AI, from the “model” mode to real-world use to affect clinical outcomes.

“Although 2020 was our inaugural year, CHIL is already emerging as an essential venue for researchers exploring how computing can improve various facets of the healthcare industry,” said CHIL General Chair Marzyeh Ghassemi, University of Toronto and Vector Institute. “Last year’s inaugural conference surpassed our expectations and we’re excited to build on that success in the coming years. Our field needs a dedicated forum for this highly-promising field.”

“The CHIL conference is designed to spark insight-driven discussions on new and emerging ideas that may lead to cross-disciplinary collaboration between professionals involved in computer science, health informatics, and frontline healthcare providers,” added CHIL Program Co-chair Tristan Naumann, Microsoft Research.

“Machine learning, AI and other computing technologies offer the potential to revolutionize the healthcare industry,” added CHIL Program Co-chair Emma Pierson, Cornell University and Microsoft Research. “At the same time, there’s little room for error when it comes to safety, explainability, fairness, and accuracy. The papers and presentations being presented at CHIL seek to identify, and in many cases rectify, the challenges we face in improving healthcare systems.”

ACM CHIL 2021 features:

  • 6 keynote presenters
  • 5 tutorials
  • More than 25 research papers


Keynote Presentations:

AI for Drug Discovery: Challenges and Opportunities
Regina Barzilay, MIT Computer Science & Artificial Intelligence Lab

Machine Learning in Healthcare: From Modeling to Clinical Impact
Narges Razavian, New York University Langone Medical Center

Holding a Hammer When There Are No Nails - Rapid Iteration to Build COVID-19 Support Programs for Historically Marginalized Communities"
Mark Sendak, Duke Institute for Health Innovation

Lessons on the Path from Code to Clinic - Some Common Myths in Machine Learning for Healthcare
Alan Karthikesalingam, Google Health (London)

Bringing AI to the Bedside with User Centered Design
Maia Jacobs, Northwestern University

Precision Medicine with Imprecise EHR Data
Tianxi Cai, Harvard Medical School

Research Papers
A total of 27 research papers, including the ability to automate the drawing of information from electronic health records, to trustworthy machine learning, will be presented.


Five tutorials address a range of subjects, from Explainable AI to the challenges of creating mobile health intervention systems.

About ACM

ACM, the Association for Computing Machinery, is the world's largest educational and scientific computing society, uniting educators, researchers, and professionals to inspire dialogue, share resources, and address the field's challenges. ACM strengthens the computing profession's collective voice through strong leadership, promotion of the highest standards, and recognition of technical excellence. ACM supports the professional growth of its members by providing opportunities for life-long learning, career development, and professional networking.

Jim Ormond

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