ReviewAfrican journal of laboratory medicine2024
Impact of artificial intelligence and digital technology-based diagnostic tools for communicable and non-communicable diseases in Africa.
Review in African journal of laboratory medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) and digital technology, as advanced human-created tools, are influencing the healthcare sector. Aim: This review provides a comprehensive and structured exploration of the opportunities presented by AI and digital technology to laboratory diagnostics and management of communicable and non-communicable diseases in Africa. Methods: The study employed the Preferred Reporting Items for Systematic Reviews, Meta-Analyses guidelines and Bibliometric analysis as its methodological approach. Peer-reviewed publications from 2000 to 2024 were retrieved from PubMed Results: The study incorporated a total of 1563 peer-reviewed scientific documents and, after filtration, 37 were utilised for systematic review. The findings revealed that AI and digital technology play a key role in patient management, quality assurance and laboratory operations, including healthcare decision-making, disease monitoring and prognosis. Metadata reflected the disproportionate research outputs distribution across Africa. In relation to non-communicable diseases, Egypt, South Africa, and Morocco lead in cardiovascular, diabetes and cancer research. Representing communicable diseases research, Algeria, Egypt, and South Africa were prominent in HIV/AIDS research. South Africa, Nigeria, Ghana, and Egypt lead in malaria and tuberculosis research. Conclusion: Facilitation of widespread adoption of AI and digital technology in laboratory diagnostics across Africa is critical for maximising patient benefits. It is recommended that governments in Africa allocate more funding for infrastructure and research on AI to serve as a catalyst for innovation. What this study adds: This review provides a comprehensive and context-specific analysis of AI's application in African healthcare.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.