Diagnostic Concordance Using Japan Narrow‐band Imaging Expert Team Classification for Diagnosing Colorectal Neoplasms: A Web‐based Diagnostic Concordance Study
While the JNET classification demonstrated high diagnostic concordance for SSL/HP, variability remained in neoplastic lesions, particularly in T1b cancer. These findings highlight the need for further refinement of the classification system to improve its diagnostic concordance in clinical practice.
Authors
- Yasuhiko Mizuguchi (ORCID: https://orcid.org/0000-0003-1868-0692)
- Hideki Ishikawa (ORCID: https://orcid.org/0000-0001-5980-698X)
- Yutaka Saito (ORCID: https://orcid.org/0000-0002-9574-7451)
- Taku Sakamoto (ORCID: https://orcid.org/0000-0002-0239-4977)
- Yoshitaka Murakami (ORCID: https://orcid.org/0000-0002-8134-0327)
Institutions
- Toho University (JP)
- University of Tsukuba (JP)
- Kyoto Prefectural University of Medicine (JP)
- National Cancer Center Hospital East (JP)
- Institute of Applied Biochemistry (JP)
Publication Details
- Journal
- DEN Open
- Published
- 2025-11-14
- DOI
- https://doi.org/10.1002/deo2.70232
- Primary Topic
- AI in cancer detection
- Type
- article
- Field-Weighted Citation Impact
- 0.00