Machine learning health-related applications in low-income and middle-income countries: a scoping review protocol.

ABSTRACT:

Introduction

Machine learning (ML) has been used in bio-medical research, and recently in clinical and public health research. However, much of the available evidence comes from high-income countries, where different health profiles challenge the application of this research to low/middle-income countries (LMICs). It is largely unknown what ML applications are available for LMICs that can support and advance clinical medicine and public health. We aim to address this gap by conducting a scoping review of health-related ML applications in LMICs.

Methods and analysis

This scoping review will follow the methodology proposed by Levac et al. The search strategy is informed by recent systematic reviews of ML health-related applications. We will search Embase, Medline and Gl

SUBMITTER: Carrillo-Larco RM 

PROVIDER: S-EPMC7223147 | biostudies-literature | 2020 May

REPOSITORIES: biostudies-literature