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Transforming clinical documentation with ambient artificial intelligence (AI) scribes: a narrative review of technology, impact, and implementation.

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Bibliographic Details
Title: Transforming clinical documentation with ambient artificial intelligence (AI) scribes: a narrative review of technology, impact, and implementation.
Authors: Razaghi M; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Hafez A; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Farina JM; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Scalia IG; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Pereyra M; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Abdelfattah FE; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Sheashaa H; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Awad K; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Lester SJ; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Ayoub C; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA., Arsanjani R; Department of Cardiovascular Medicine, Mayo Clinic, Phoenix, Arizona, USA.
Source: Cardiovascular diagnosis and therapy [Cardiovasc Diagn Ther] 2026 Feb 28; Vol. 16 (1), pp. 11. Date of Electronic Publication: 2026 Jan 19.
Publication Type: Journal Article; Review
Journal Info: Publisher: AME Publishing Company Country of Publication: China NLM ID: 101601613 Publication Model: Print-Electronic Cited Medium: Print ISSN: 2223-3652 (Print) Linking ISSN: 22233652 NLM ISO Abbreviation: Cardiovasc Diagn Ther Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:2223-3652
DOI:10.21037/cdt-2025-454