Machine learning algorithms and traditional statistical models for detection of dementia: a population-based study

We developed and evaluated the performance of LR, RF and XGBoost models for dementia detection in a rural older population in China. All the three models showed excellent discrimination and calibration. The XGBoost model exhibited the best performance and clinical utility in dementia detection. These models are based on information readily available in routine clinical practice, which could be easily implemented amongst rural older populations for dementia detection.