| Autor: |
Olawande Daramola, Peter Nyasulu, Tivani Mashamba-Thompson, Thomas Moser, Sean Broomhead, Ameera Hamid, Jaishree Naidoo, Lindiwe Whati, Maritha J. Kotze, Karl Stroetmann, Victor Chukwudi Osamor |
| Jazyk: |
angličtina |
| Rok vydání: |
2021 |
| Předmět: |
|
| Zdroj: |
Informatics, Vol 8, Iss 4, p 63 (2021) |
| Druh dokumentu: |
article |
| ISSN: |
2227-9709 |
| DOI: |
10.3390/informatics8040063 |
| Popis: |
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 AI-enabled 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 self-data 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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