AI in Global Health
Cross-source consensus on AI in Global Health from 1 sources and 5 claims.
1 sources · 5 claims
Uses
Benefits
Risks & contraindications
Other
Highlighted claims
- The article defines AI as algorithms and tools that learn from data and perform tasks without explicit human input. — Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities
- The article states that AI carries substantial risks requiring responsible use. — Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities
- During COVID-19, AI supported diagnosis, prognosis, drug discovery, genomic sequencing, and vaccine development. — Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities
- NIH-funded examples included AI for tuberculosis treatment resistance, clinical decision support, and anal precancer detection among people living with HIV. — Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities
- AI is framed as potentially transformative for health systems in resource-constrained settings. — Use of artificial intelligence for health science in low- and middle-income countries: NIH portfolio landscape, gaps and opportunities