Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

< Back to Article

Can machine-learning improve cardiovascular risk prediction using routine clinical data?

Table 3

Top 10 risk factor variables for CVD algorithms listed in descending order of coefficient effect size (ACC/AHA; logistic regression), weighting (neural networks), or selection frequency (random forest, gradient boosting machines).

Algorithms were derived from training cohort of 295,267 patients.

Table 3

doi: https://doi.org/10.1371/journal.pone.0174944.t003