A scoping methodological review of simulation studies comparing statistical and machine learning approaches to risk prediction for time-to-event data.

ABSTRACT:

Background

There is substantial interest in the adaptation and application of so-called machine learning approaches to prognostic modelling of censored time-to-event data. These methods must be compared and evaluated against existing methods in a variety of scenarios to determine their predictive performance. A scoping review of how machine learning methods have been compared to traditional survival models is important to identify the comparisons that have been made and issues where they are lacking, biased towards one approach or misleading.

Methods

We conducted a scoping review of research articles published between 1 January 2000 and 2 December 2020 using PubMed. Eligible articles were those that used simulation studies to compare statistical and machine learning methods

SUBMITTER: Smith H 

PROVIDER: S-EPMC9161606 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature