Work

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

Year: 2021

Type: article

Source: Nature Electronics

DOI: 10.1038/s41928-021-00612-x

Authors: Xin Guo, Muhammad Arslan Khalid, Ivo Domingos, Anna Lito Michala, Moses Adriko, Candia Rowel, Diana Ajambo, Alice Garrett, Shantimoy Kar, Xiaoxiang Yan, Julien Reboud, Edridah M. Tukahebwa, Jonathan M. Cooper

Institutions: University of Glasgow, Ministry of Health

Language: English

Topic: Biosensors and Analytical Detection

Subfield: Biomedical Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Good health and well-being, Industry, innovation and infrastructure, Reduced inequalities

Open Access status: bronze

Funders: National Institute for Health and Care Research, Scottish Funding Council, Research Councils UK, China Scholarship Council, Engineering and Physical Sciences Research Council

Awards: Novel low cost diagnostic tools and their impact in Africa, Mobile Phone enabled Diagnostics for Infectious Disease Diagnosis: Low Cost Tools for Digital Health in East Africa, DTP 2016-2017 University of Glasgow, G3855426696, G4761716424, G5331123958, G8206736273, G8572525257, G8966523210, G8974483447

OpenAlex ID: W3191982151

FWCI: 5.621

Cites: 36

Cited by: 101

Related to: 10