Artificial intelligence in cancer screening: a narrative review of current evidence and future directions
AI is beginning to move beyond experimental settings and into real-world clinical practice. Early evidence suggests that it can enhance both accuracy and efficiency. At the same time, important challenges remain, including risks of bias, overdiagnosis, and uneven performance across clinical environments. However, sustainable progress will require robust validation, careful integration into clinical workflows, and policies that ensure the technology benefits patients across diverse settings.
Authors
- Gamze Sönmez
- Yiğit Yazarkan (ORCID: https://orcid.org/0009-0000-8989-5207)
- Deniz Can Güven (ORCID: https://orcid.org/0000-0002-6924-9467)
- Taha Koray Sahin
- Alessandro Rizzo
Institutions
- Istituto Tumori Bari (IT)
- Hacettepe University (TR)
Publication Details
- Journal
- Expert Review of Molecular Diagnostics
- Published
- 2026-03-23
- DOI
- https://doi.org/10.1080/14737159.2026.2648127
- Primary Topic
- Artificial Intelligence in Healthcare and Education
- Type
- article
- Field-Weighted Citation Impact
- 0.00