aceKey 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…
AI systems in healthcare have seen limited successful deployment into clinical practice due to intrinsic machine learning limitations and implementation barriers
No quantified deployment rate, patient outcomes, or specific clinical sites reported in supplied text
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
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Truvace Impact Record TRV-2026-0059, v7: “Key challenges for delivering clinical impact with artificial intelligence.” Truvace, 2026-07-13. /record/TRV-2026-0059 (accessed at citation time). sha256 1f5072b1e37453c8…
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