Smartphone-based DNA diagnostics for malaria detection using deep learning for local decision support and blockchain technology for security

Guo, X. et al. (2021) Smartphone-based DNA diagnostics for malaria detection using deep learning for local decision support and blockchain technology for security. Nature Electronics, 4(8), pp. 615-624. (doi: 10.1038/s41928-021-00612-x)

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Abstract

In infectious disease diagnosis, results need to be communicated rapidly to healthcare professionals once testing has been completed so that care pathways can be implemented. This represents a particular challenge when testing in remote, low-resource rural communities, in which such diseases often create the largest burden. Here, we report a smartphone-based end-to-end platform for multiplexed DNA diagnosis of malaria. The approach uses a low-cost paper-based microfluidic diagnostic test, which is combined with deep learning algorithms for local decision support and blockchain technology for secure data connectivity and management. We validated the approach via field tests in rural Uganda, where it correctly identified more than 98% of tested cases. Our platform also provides secure geotagged diagnostic information, which creates the possibility of integrating infectious disease data within surveillance frameworks.

Item Type:Articles
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Guo, Xin and Domingos, Mr Ivo and Kar, Dr Shantimoy and Garrett, Miss Alice and Khalid, Muhammad and Michala, Dr Lito and Yan, Dr Xiaoxiang and Cooper, Professor Jonathan and Reboud, Dr Julien
Authors: Guo, X., Khalid, M. A., Domingos, I., Michala, A. L., Adriko, M., Rowell, C., Ajambo, D., Garrett, A., Kar, S., Yan, X., Reboud, J., Tukahebwa, E. M., and Cooper, J. M.
College/School:College of Science and Engineering > School of Computing Science
College of Science and Engineering > School of Engineering > Biomedical Engineering
Journal Name:Nature Electronics
Publisher:Nature Research
ISSN:2520-1131
ISSN (Online):2520-1131
Published Online:02 August 2021
Copyright Holders:Copyright © 2021 The Authors
First Published:First published in Nature Electronics 4(8): 615-624
Publisher Policy:Reproduced in accordance with the publisher copyright policy
Related URLs:
Data DOI:10.5525/gla.researchdata.1106

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Project CodeAward NoProject NamePrincipal InvestigatorFunder's NameFunder RefLead Dept
302017EPSRC GCRF ISA 2017 - University of GlasgowLynne McCorristonEngineering and Physical Sciences Research Council (EPSRC)EP/R512813/1S&E - Business Development
300573Novel low cost diagnostic tools and their impact in AfricaJonathan CooperEngineering and Physical Sciences Research Council (EPSRC)EP/R01437X/1ENG - Biomedical Engineering
309827Mobile Phone enabled Diagnostics for Infectious Disease Diagnosis: Low Cost Tools for Digital Health in East AfricaJonathan CooperEngineering and Physical Sciences Research Council (EPSRC)EP/T029765/1ENG - Biomedical Engineering
172865EPSRC DTP 16/17 and 17/18Tania GalabovaEngineering and Physical Sciences Research Council (EPSRC)EP/N509668/1Research and Innovation Services