research Early prediction of alopecia areata using machine learning modeling of neuro stress immune signatures from multi datasets
In this study, researchers developed a predictive model for the onset of alopecia areata by analyzing six datasets to identify key feature genes and employing various machine learning algorithms, ultimately finding the XGBoost model most effective for clinical application.
