Key challenges for delivering clinical impact with artificial intelligence
BACKGROUND: Artificial intelligence (AI) research in healthcare is accelerating rapidly, with potential applications being demonstrated across various domains of medicine. However, there are currently limited examples of such techniques being successfully deployed into clinical practice. This article explores the main challenges and limitations of AI in healthcare, and considers the steps required to translate these potentially transformative technologies from research to clinical practice. MAIN BODY: Key challe…
Key challenges for delivering clinical impact with artificial intelligence: However, there are currently limited examples of such techniques being successfully deployed into clinical practice.
Historical evidence reading: the cited study may be limited by its design, population, period, or setting, and later research may report different effects.
Evidence
- Peer-reviewedInternational Journal of Information Management2019-08-27
- Peer-reviewedJournal of Big Data2021-03-31
- Peer-reviewedIEEE Access2020-01-01
- Peer-reviewedBMC Medicine2019-10-29
- Peer-reviewedInforming Science: The International Journal of an Emerging Transdiscipline2023-01-01
Truvace Impact Record TRV-2026-0059, v6: “Key challenges for delivering clinical impact with artificial intelligence.” Truvace, 2026-07-12. /record/TRV-2026-0059 (accessed at citation time). sha256 00f081c72fe6f9eb…
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