Predicting population health with machine learning: a scoping review.

ABSTRACT:

Objective

To determine how machine learning has been applied to prediction applications in population health contexts. Specifically, to describe which outcomes have been studied, the data sources most widely used and whether reporting of machine learning predictive models aligns with established reporting guidelines.

Design

A scoping review.

Data sources

MEDLINE, EMBASE, CINAHL, ProQuest, Scopus, Web of Science, Cochrane Library, INSPEC and ACM Digital Library were searched on 18 July 2018.

Eligibility criteria

We included English articles published between 1980 and 2018 that used machine learning to predict population-health-related outcomes. We excluded studies that only used logistic regression or were restricted to a clinical context.

Data extraction and

SUBMITTER: Morgenstern JD 

PROVIDER: S-EPMC7592293 | biostudies-literature | 2020 Oct

REPOSITORIES: biostudies-literature