Clinical Impact of Artificial Intelligence–Augmented Lymph Node Evaluation in Metastatic Gastric, Colorectal, and Breast Cancer
The AI module improved pathologists' sensitivity in detecting LN metastases and significantly reduced review time, particularly for positive nodes. These findings support the integration of AI tools to enhance diagnostic efficiency and accuracy in routine pathology practice.
Authors
- Kaveh Taghipour (ORCID: https://orcid.org/0000-0002-3839-2607)
- Wai Po Kevin Teng
- Jijgee Munkhdelger (ORCID: https://orcid.org/0000-0003-3483-2342)
- Andrey Bychkov (ORCID: https://orcid.org/0000-0002-4203-5696)
- Sahil Ajit Saraf
- Kris Lami (ORCID: https://orcid.org/0000-0001-9191-3339)
- Shion Ando (ORCID: https://orcid.org/0000-0002-9013-3514)
- A. Abdelmaboud Abbas
- Yogesh Pratap Singh
- Junya Fukuoka
Institutions
- University of Nagasaki (JP)
- SingHealth (SG)
- Singapore General Hospital (SG)
- Kameda Medical Center (JP)
- Sarasota Memorial Hospital (US)
- ABB (Canada) (CA)
- Nagasaki University (JP)
Publication Details
- Journal
- Archives of Pathology & Laboratory Medicine
- Published
- 2026-02-09
- DOI
- https://doi.org/10.5858/arpa.2025-0388-oa
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00