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Transformers-based models in healthcare are rapidly reconceptualizing the development of medical AI systems. These models can be adapted to a variety of downstream tasks by processing an extensive set of data, enhancing personalized medicine, improving diagnosis and treatment plans, and creating synthetic data for research while maintaining privacy. The goal of this conference is to advance technological research and provide solutions for the soft and hard challenges of integrating and developing AI systems in public health.

Key Research Questions:

1. How can we build robust and multimodal models in healthcare to advance clinical decision-making or biomedical treatments?

2. How can we build human-in-the-loop AI systems for a complex set of stakeholders?

3. How can research in AI and public health support the advancement of the adoption of systems in public health departments?

curated by Prof. Aldo Faisal (University of Bayreuth / Imperial College London)

The Meeting will be held under Chatham House Rules.