Key challenges for delivering clinical impact with artificial intelligence
Kelly CJ, Karthikesalingam A, Suleyman M et al. · 2019
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Description
Catherine Kelly, Alan Karthikesalingam, Mustafa Suleyman, and coauthors listed challenges for clinical artificial intelligence in 2019. Health AI research was racing ahead, with demos across many branches of medicine. Yet very few tools had reached real clinical use.
The authors name the gaps: messy real-world data, workflow fit, regulation, and proof of benefit. They warn that models trained in one hospital may fail in another. Fairness and monitoring after launch get equal weight with accuracy. The paper became a sober checklist for teams moving AI from papers to wards. The authors also address who stays accountable when an algorithm's advice is followed or ignored.
Catalog record
| CREATOR | Kelly CJ, Karthikesalingam A, Suleyman M et al. |
|---|---|
| YEAR | 2019 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 30 KB |
| LICENSE | Creative Commons Attribution License |
| RIGHTS | CC BY |
| SOURCE | PubMed Central |