Can AI safely automate medical decision-making tasks to improve patient outcomes? In this session, learn about the development and translation challenges for medical AI and how researchers are addressing them through a blend of innovation in algorithm development, dataset curation, and implementation design. Learn about self-supervised learning methods for medical image classification and open benchmarks that can help the community transparently measure advancements in the generalizability of algorithms to new geographies, patient populations, and clinical settings. Explore key ways in which we can realize the potential of medical AI to make healthcare more accurate, efficient, and accessible for patients worldwide.


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