Integrating Machine Learning Boosts Disease Prediction Accuracy

A recent review explored how integrating machine learning with traditional statistical models can enhance disease risk prediction accuracy, a key tool in clinical decision-making. While traditional models like logistic regression are limited by certain assumptions, machine learning offers flexibility but has inconsistent results in some cases. The study revealed that combined models, especially stacking methods, outperform individual methods by harnessing each approach's strengths and addressing...