This fundamental (and quite reasonable) limitation of any machine learning technique is addressed by feature selection: choosing a good set of features upon which to build models.

Ultimately, these techniques could make machine learning more accessible. Although automated machine learning has been around for almost a decade, researchers are still working to refine it.

Our findings suggest that integrating machine learning into traditional statistical methods can provide more accurate and generalizable models for disease risk prediction.