Causal machine learning with interpretability deciphers the impact of micropollutants and socioeconomic factors on ARGs in Chinese urban drinking water | Synapse
March 3, 2026
Causal machine learning with interpretability deciphers the impact of micropollutants and socioeconomic factors on ARGs in Chinese urban drinking water
Key Points
Antibiotic resistance genes are influenced by both micropollutants and socioeconomic factors.
The study identifies significant correlations, such as higher levels of certain micropollutants affecting ARG prevalence.
Causal machine learning methods enhance interpretability, allowing for better understanding of these complex interactions.
Findings underscore potential environmental health risks, warranting further investigation into urban water safety.