The use of generative artificial intelligence–based dictation in a neurosurgical practice: a pilot study
An AI-based model performed at a noninferior rate compared to a commercially available speech-to-text dictation program. Generative models provide potential benefits such as contextual inference that show promise in limiting errors with increased dictation speed or adjustment for impure input data.
Authors
- John D. Carmichael (ORCID: https://orcid.org/0000-0002-3194-9249)
- David J. Coté (ORCID: https://orcid.org/0000-0001-5419-1517)
- Lawrance K. Chung (ORCID: https://orcid.org/0009-0008-6410-9490)
- William J. Mack (ORCID: https://orcid.org/0000-0003-0970-2546)
- Jonathan Dallas (ORCID: https://orcid.org/0000-0003-0202-2003)
- Hung‐Chun Yu (ORCID: https://orcid.org/0000-0002-4980-8508)
- John C. Liu
- Ishan Shah (ORCID: https://orcid.org/0000-0003-2249-1827)
- Robert G. Briggs (ORCID: https://orcid.org/0000-0001-9329-4471)
- Gabriel Zada (ORCID: https://orcid.org/0000-0001-5821-902X)
- David Gómez (ORCID: https://orcid.org/0000-0003-3612-661X)
- Benjamin S. Hopkins (ORCID: https://orcid.org/0000-0002-9493-2110)
Institutions
- University of Southern California (US)
Publication Details
- Journal
- Neurosurgical FOCUS
- Published
- 2025-07-01
- DOI
- https://doi.org/10.3171/2025.4.focus24834
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00