Harnessing Artificial Intelligence in Health Research in Low-Income and Middle-Income Countries: Potential and Caution
Siphamandla Bonga Gumede, Willem Daniel F. Venter, Nolwazi Mndebele, Samanta Tresha Lalla-Edward · 2026
Read Harnessing Artificial Intelligence in Health Research in Low-Income and Middle-Income Countries: Potential and Caution by Siphamandla Bonga Gumede, Willem Daniel F. Venter, Nolwazi Mndebele, Samanta Tresha Lalla-Edward (2026) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-13319667.txt.
Description
Siphamandla Bonga Gumede and co-authors offer, in 2026, a cautious assessment of artificial intelligence in health research across low-income and middle-income countries. Staff shortages, fragmented data and weak infrastructure make the potential gains large. Early uses include finding people at high risk of HIV and supporting long-term disease care.
Many models, however, are built and tested in wealthy settings, with little regard for local disease patterns, data quality or infrastructure. Bias, opacity and weak evidence of real-world benefit are recurring concerns. Consent, data governance and community engagement also receive too little attention, the authors argue. Drawing on work in HIV, chronic disease and trial research, they urge implementation science and ethical alignment so tools serve local priorities rather than imported assumptions.
Catalog record
| CREATOR | Siphamandla Bonga Gumede, Willem Daniel F. Venter, Nolwazi Mndebele, Samanta Tresha Lalla-Edward |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 28 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |