Toward More Practical Causal Epidemiology and Health Risk Assessment Using Causal Artificial Intelligence
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-32013-2_11
Reference74 articles.
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2. Ankan A, Wortel IMN, Textor J (2021 Feb) Testing graphical causal models using the R package “dagitty”. Curr Protoc 1(2):e45. https://doi.org/10.1002/cpz1.45
3. Apley DW, Zhu J (2020) Visualizing the effects of predictor variables in black box supervised learning models. J R Stat Soc 82:869–1164
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5. Bareinboim E, Pearl J (2013) Causal transportability with limited experiments. In: Proceedings of the 27th AAAI Conference on Artificial Intelligence, pp 95–101. ftp://ftp.cs.ucla.edu/pub/stat_ser/r408.pdf
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