Ethical Pitfalls in AI‐Based Predictive Models in Surgery
The integration of predictive models into surgery requires more than technical excellence, and it demands ethical vigilance. Preparing future clinicians through education that emphasizes both clinical reasoning and ethical awareness is critical. By aligning predictive model development with human-centered values, healthcare systems can ensure that these innovations enhance surgical practice while safeguarding equity, transparency, and patient trust.
Authors
- Marieke Bak (ORCID: https://orcid.org/0000-0003-0655-0743)
- J. Carel Goslings (ORCID: https://orcid.org/0000-0003-3942-0304)
- E.J.M. Nieveen van Dijkum (ORCID: https://orcid.org/0000-0002-3029-6071)
- Stephen Rainey (ORCID: https://orcid.org/0000-0002-5540-6046)
- Freek Daams (ORCID: https://orcid.org/0000-0001-6323-6342)
- Mark Schakel
- Geert Kazemier
- B.P. Keller
- Sara Ben Hmido (ORCID: https://orcid.org/0009-0004-9893-8407)
- Houssam Abder Rahim
- Corrette Ploem
Institutions
- OLVG (NL)
- Amsterdam Neuroscience (NL)
- Amsterdam University Medical Centers (NL)
- Cancer Center Amsterdam (NL)
- University of Amsterdam (NL)
- Delft University of Technology (NL)
Publication Details
- Journal
- World Journal of Surgery
- Published
- 2025-09-04
- DOI
- https://doi.org/10.1002/wjs.70080
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 2.62
Funders
- Medtronic Europe