Receiver operating characteristic analysis of machine learning model, risk scores and internal medicine physicians.

van Doorn, William P. T. M.; Stassen, Patricia M.; Borggreve, Hella F.; Schalkwijk, Maaike J.; Stoffers, Judith; Bekers, Otto; Meex, Steven J. R.

doi:10.1371/journal.pone.0245157.s013

pone.0245157.s013.docx (216.41 kB)

Receiver operating characteristic analysis of machine learning model, risk scores and internal medicine physicians.

journal contribution

posted on 2021-01-19, 18:27 authored by William P. T. M. van Doorn, Patricia M. Stassen, Hella F. Borggreve, Maaike J. Schalkwijk, Judith Stoffers, Otto Bekers, Steven J. R. Meex

Receiver operating characteristics analysis of the lab + clinical machine learning model (AUC: 0.852 [0.783–0.922]), abbMEDS (0.631 [0.537–0.726]), mREMS (0.630 [0.535–0.724]) and internal medicine physicians (mean 0.735 [0.648–0.821]). Internal medicine physicians were depicted as bullets in the ROC analysis.

(DOCX)