Please use this identifier to cite or link to this item: http://hdl.handle.net/11189/9016
Title: Towards ai-enabled multimodal diagnostics and management of covid-19 and comorbidities in resource-limited settings
Authors: Daramola, Olawande 
Nyasulu, Peter 
Mashamba-Thompson, Tivani 
Moser, Thomas 
Broomhead, Sean 
Hamid, Ameera 
Naidoo, Jaishree 
Whati, Lindiwe 
Kotze, Maritha J. 
Stroetmann, Karl 
Osamor, Victor Chukwudi 
Keywords: Artificial intelligence;COVID-19;resource-limited settings;multimodal diagnostics;diagnostics;machine learning;explainable AI;point-of-care
Issue Date: 2021
Publisher: MDPI
Source: Daramola, O., Nyasulu, P., Mashamba-T.T. et al. 2021. Towards ai-enabled multimodal diagnostics and management of covid-19 and comorbidities in resource-limited settings. Informatics, 8(63): 1-13. [https://doi.org/10.3390/ informatics8040063]
Journal: Informatics 
Abstract: A conceptual artificial intelligence (AI)-enabled framework is presented in this study involving triangulation of various diagnostic methods for management of coronavirus disease 2019 (COVID-19) and its associated comorbidities in resource-limited settings (RLS). The proposed AIenabled framework will afford capabilities to harness low-cost polymerase chain reaction (PCR)-based molecular diagnostics, radiological image-based assessments, and end-user provided information for the detection of COVID-19 cases and management of symptomatic patients. It will support selfdata capture, clinical risk stratification, explanation-based intelligent recommendations for patient triage, disease diagnosis, patient treatment, contact tracing, and case management. This will enable communication with end-users in local languages through cheap and accessible means, such as WhatsApp/Telegram, social media, and SMS, with careful consideration of the need for personal data protection. The objective of the AI-enabled framework is to leverage multimodal diagnostics of COVID-19 and associated comorbidities in RLS for the diagnosis and management of COVID-19 cases and general support for pandemic recovery. We intend to test the feasibility of implementing the proposed framework through community engagement in sub-Saharan African (SSA) countries where many people are living with pre-existing comorbidities. A multimodal approach to disease diagnostics enabling access to point-of-care testing is required to reduce fragmentation of essential services across the continuum of COVID-19 care.
URI: http://hdl.handle.net/11189/9016
ISSN: 2227-9709
DOI: https://doi.org/10.3390/ informatics8040063
Appears in Collections:FID - Journal Articles (DHET subsidised)

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