Machine Learning for Health (ML4H) brings together machine learning researchers, clinicians, and healthcare data experts. In this year's program, invited speakers and attendees will be able to discuss the utility and challenges of XAI as well as paths to practice for ML in healthcare. The two focus sessions are accompanied by keynotes (see all invited speakers here) as well as interactive research roundtables, two poster sessions, and datathon presentations. As usual, ML4H also publishes proceedings of accepted full papers in PMLR.

ML4H 2022 has concluded for this year. Thank you to all speakers, sponsors, and attendees for helping make ML4H 2022 such a success. Congratulations to our best papers:

• "Predicting Treatment Adherence of Tuberculosis Patients at Scale ": Mihir Kulkarni, Satvik Golechha, Rishi Raj Grandhe, Jithin K. Sreedharan, Ankit Bhardwaj, Santanu Rathod, Bhavin Vadera, Jayakrishna Kurada, Kirankumar Rade, Sanjay Mattoo, Rajendra Joshi, Alpan Raval

• "Precise Clinical Predictions via Counterfactual and Factual Reasoning over Hypergraphs of Electronic Health Records": Ran Xu, Yue Yu, Chao Zhang, Mohammed K Ali, Joyce Ho, Carl Yang

For questions/comments, email us at ml4h.2022@gmail.com. For announcements, follow us on Twitter @symposiumml4h.

Speakers include:

Berkman Sahiner

FDA Center for Devices and Radiological Health (CDRH)
Senior Biomedical Research Scientist

Benjamin Recht

University of California, Berkeley
Associate Professor

Nicola Pezzotti

Philips Research
Senior Scientist and Project Lead
Eindhoven University of Technology
Assistant Professor

Mihaela van der Schaar

University of Cambridge
Professor

Himabindu (Hima) Lakkaraju

Harvard University
Assistant Professor

Emmanuel Candès

Stanford University
Professor

Zachary Lipton

Carnegie Mellon University
Assistant Professor

Edwin Fong

Novo Nordisk
Data Scientist

Platinum Sponsors

Silver Sponsors

Insitro