Real-World Evidence
Cross-source consensus on Real-World Evidence from 1 sources and 5 claims.
1 sources · 5 claims
Uses
How it works
Evidence quality
Where it comes from
Highlighted claims
- Real-world evidence is clinical evidence about the usage, risks, and benefits of medical products generated through analysis of real-world data. — Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review
- Real-world evidence can inform drug development, regulatory decisions, health technology assessment, clinical decisions, and patient decisions. — Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review
- Real-world data sources include electronic health records, administrative claims, patient registries, direct-to-participant studies, and other routinely collected healthcare datasets. — Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review
- There is no published overview of the range of generative AI applications, methods, performance evaluations, risks, or opportunities in the real-world evidence domain. — Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review
- Generative AI potential uses in real-world evidence include participant recruitment, data extraction from studies, drug safety surveillance analysis, epidemic modelling, and streamlining literature reviews. — Applications of artificial intelligence for real-world evidence generation: a protocol for a living scoping review