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Causal machine learning for extracting insights from observational radiotherapy data

npj Digital Medicine, Published online: 14 September 2026; doi:10.1038/s41746-026-03214-z

While clinical trials are the gold standard for determining causative side effects from treatment, some trials are too logistically or ethically challenging to complete. Many side effects of treatments are learned from retrospective analyses; however, these can be confounded by other random variables. Causal and explainable machine learning tools are promising for teasing apart confounders from real treatment side effects in observational data.
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