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Introduction
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How is the state of AI deployment
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What do radiologists think about AI
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How does AI affect radiologists
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How can AI be used in healthcare
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How can AI be used in modelling
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Data infrastructure
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Health data poverty
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Trust issue
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Barriers to implementation
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Trust and transparency
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How to encourage transparency
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The potential of AI
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Paul Elliott
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DeepMind
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Training the next generation of researchers
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Developing multidisciplinary people
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AI failure
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Barriers to AI integration
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Regulation
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Wrap up
Description:
Explore the challenges and potential of AI in pandemic response through this academic panel discussion featuring health AI specialists. Examine why AI had limited impact during COVID-19, analyze data science hurdles in healthcare, and uncover lessons learned for future crisis management. Gain insights into the strengths and weaknesses of AI applications in epidemiology, radiology, and healthcare modeling. Delve into critical issues such as data infrastructure, health data poverty, trust, transparency, and regulatory barriers. Discover strategies for training multidisciplinary researchers and integrating AI effectively in healthcare systems. Learn from expert perspectives on AI failures, implementation challenges, and the future potential of AI in addressing global health crises.

Is There a Post-Pandemic AI Panacea

Alan Turing Institute
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