The Framing of machine learning risk prediction models illustrated by evaluation of sepsis in general wards

Abstract Problem framing is critical to developing risk prediction models because all subsequent development work and evaluation takes place within the context of how a problem has been framed and explicit documentation of framing choices makes it easier to compare evaluation metrics between publish...

Full description

Saved in:
Bibliographic Details
Main Authors: Simon Meyer Lauritsen, Bo Thiesson, Marianne Johansson Jørgensen, Anders Hammerich Riis, Ulrick Skipper Espelund, Jesper Bo Weile, Jeppe Lange
Format: article
Language:EN
Published: Nature Portfolio 2021
Subjects:
Online Access:https://doaj.org/article/951bd4e1777041f6af156aa4d5aa40ac
Tags: Add Tag
No Tags, Be the first to tag this record!