Analysis of epidemiological association patterns of serum thyrotropin by combining random forests and Bayesian networks

Approaching epidemiological data with flexible machine learning algorithms is of great value for understanding disease-specific association patterns. However, it can be difficult to correctly extract and understand those patterns due to the lack of model interpretability. We here propose a machine l...

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