XGBoost trained on single-cell islet gene expression from GEO reports 97% accuracy in separating Type 2 diabetes from non-diabetic cells, but the result depends on a cell-level split that may leak donor information.
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Leveraging Gene Expression Data and Explainable Machine Learning for Enhanced Early Detection of Type 2 Diabetes
XGBoost trained on single-cell islet gene expression from GEO reports 97% accuracy in separating Type 2 diabetes from non-diabetic cells, but the result depends on a cell-level split that may leak donor information.