Abstract
The application of artificial intelligence (AI) in health, and specifically to diagnostic tools that target high burden global diseases, is an emerging area, where only a limited number of products have achieved regulatory approval and the ability to scale.
Diagnostic tools that incorporate AI may be of value in resource-limited settings, especially given the known shortage of healthcare workers and diagnostic infrastructure in these settings. Whilst the results of projects exploring such use cases have been published in academic literature, the technology has only recently started to be used on a wider scale.
Comprehensive information on commercially available AI-assisted respiratory diagnostics that can be used to target high burden global diseases in low- and middle-income countries (LMICs) is not readily available. FIND has already worked in the space of computer-aided detection for chest radiograph (CXR-CAD) evaluation and there is interest in understanding the broader AI diagnostics market, where there are promising new tools. As a result, FIND commissioned this landscape, undertaken in 2022, to identify potential solutions and technologies that utilise AI to produce a diagnostic result for tuberculosis (TB), coronavirus disease 2019 (COVID-19), or pneumonia in LMICs. The aim of this report is to inform policymakers, healthcare providers, researchers, and patients, by providing an overview of the field, and to enable stakeholders to identify those technologies that may be most fit for their use.