<scp>AI</scp>‐driven simplification of surgical reports in gynecologic oncology: A potential tool for patient education
Advanced language models like GPT-4 can transform unedited surgical reports to improve clarity about the procedure and its outcomes. It offers considerable promise for enhancing patient education. However, concerns about medical precision underscore the need for rigorous oversight to safely integrate AI into patient education. Over the medium term, AI-generated, simplified versions of these reports-and other medical records-could be effortlessly integrated into standard automated postoperative care and digital discharge systems.
Authors
- M Riedel (ORCID: https://orcid.org/0000-0002-9524-1514)
- Caroline Riedel
- Marion B. Kiechle (ORCID: https://orcid.org/0000-0003-4237-2657)
- Fabian Riedel (ORCID: https://orcid.org/0000-0002-9693-2667)
- Bastian Meyer (ORCID: https://orcid.org/0000-0001-7634-9362)
- Niklas Amann (ORCID: https://orcid.org/0009-0005-5280-2800)
- R.D. Rubens
Institutions
- Friedrich-Alexander-Universität Erlangen-Nürnberg (DE)
- Heidelberg University (DE)
- University Hospital Heidelberg (DE)
- Helmholtz Zentrum München (DE)
- Technical University of Munich (DE)
Publication Details
- Journal
- Acta Obstetricia Et Gynecologica Scandinavica
- Published
- 2025-05-14
- DOI
- https://doi.org/10.1111/aogs.15123
- Citations
- 3
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 1.96