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1
Intro
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Exercise
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Decisionmaking tools
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Causal assumptions
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Lack of positivity
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Random positivity violations
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Poor overlap
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Linear vs quadratic
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Pneumonia example
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Two more challenges
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Conclusion
Description:
Explore the intersection of AI prediction algorithms and causal inference in this 24-minute workshop video from the Alan Turing Institute. Delve into the limitations of traditional prediction methods and discover how causal inference can enhance decision-making capabilities. Learn about counterfactual prediction and its applications in healthcare and fairness assessments. Examine methodological challenges and potential solutions presented by a team of twelve academics specializing in predictive modeling, machine learning, and causal inference. Gain insights into decision support tools for scenarios like the COVID-19 pandemic. Cover topics including decision-making tools, causal assumptions, positivity violations, overlap issues, and real-world examples such as pneumonia treatment decisions.

Theory and Methods Challenges in Counterfactual Prediction - Karla Diaz-Ordaz

Alan Turing Institute
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