ReviewHealth SA = SA Gesondheid2025
Use of artificial intelligence in healthcare in South Africa: A scoping review.
Review in Health SA = SA Gesondheid, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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
2 citing papers in PubMed.
- International standards and good practice guidelines in traditional, complementary and integrative medicine: a scoping review.Frontiers in pharmacology · 2026Article
- Artificial Intelligence in Cardiopulmonary Resuscitation: Revolutionizing Resuscitation Through Precision and Prediction - A Narrative Review.Vascular health and risk management · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Artificial intelligence (AI) transformed healthcare worldwide and has the potential to address challenges faced in the South African healthcare sector, such as limited public institutional capacity, staff shortages, and variability in skills levels that exacerbate the demand on the healthcare system that can lead to compromised care and patient safety. Aim: This study aimed to describe how AI, especially machine learning is used in healthcare in South Africa over the last 5 years. Method: The Joanna Briggs Institute (JBI) methodology for scoping reviews was used. Peer-reviewed articles in English, which were published from 2020 to date were sourced and reviewed using the Population, Concept, Context (PCC) framework. Results: A total of 35 articles were selected. The results showed a focus on conventional machine learning, a health focus on HIV and/or tuberculosis (TB) and cancer, and a lack of big data in fields other than cancer. Conclusion: There has been an increase in the use of machine learning in the analysis of health data, but access to big data appears to be a challenge. Contribution: There is a need to have access to high-quality big data, inclusive policies that promote access to the benefits of using machine learning in healthcare, and AI literacy in the health sector to understand and address ethical implications.
Indexed as
Identifiers
What Socratic 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 Socratic graph.