Table 1.

A brief comparison of regression and machine learning

	Regression	Machine learning
Mathematical assumptions	Several	Usually fewer
Analyzing high-dimensional data (e.g., >10,000 variables)	Possible, but labor intensive	Capable
Analyzing non-tabular data (e.g., images, clinical notes, etc)	Limited	Capable, but often requires extensive labor/resources
Model interpretability	Fully transparent and human-readable	Limited or absent
Ability to incorporate prior clinical/biological knowledge	Capable (e.g., assisted variable selection)	Limited or absent
Hypothesis testing	Built-in	Limited or absent