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Review
. 2021 Apr 29:4:553987.
doi: 10.3389/frai.2021.553987. eCollection 2021.

Deep Learning and its Application for Healthcare Delivery in Low and Middle Income Countries

Douglas Williams  1 , Heiko Hornung  2 , Adi Nadimpalli  3 , Ashton Peery  4
Affiliations
Review

Deep Learning and its Application for Healthcare Delivery in Low and Middle Income Countries

Douglas Williams et al. Front Artif Intell. .

Abstract

As anyone who has witnessed firsthand knows, healthcare delivery in low-resource settings is fundamentally different from more affluent settings. Artificial Intelligence, including Machine Learning and more specifically Deep Learning, has made amazing advances over the past decade. Significant resources are now dedicated to problems in the field of medicine, but with the potential to further the digital divide by neglecting underserved areas and their specific context. In the general case, Deep Learning remains a complex technology requiring deep technical expertise. This paper explores advances within the narrower field of deep learning image analysis that reduces barriers to adoption and allows individuals with less specialized software skills to effectively employ these techniques. This enables a next wave of innovation, driven largely by problem domain expertise and the creative application of this technology to unaddressed concerns in LMIC settings. The paper also explores the central role of NGOs in problem identification, data acquisition and curation, and integration of new technologies into healthcare systems.

Keywords: NGOs; artificial intelligence; deep learning; digital health; global health; machine learning; point of care diagnosis.

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Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

Figure 1
Figure 1
Typical 2D convolutional neural network. Image Source: By Aphex34 - Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=45679374.
Figure 2
Figure 2
Sample chest X-ray images. Image source: Kermany (2018).
See this image and copyright information in PMC

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