Comparative Performance of 3 Artificial Intelligence Systems for Lung Nodule Characterization in Low-Dose Computed Tomography Screening
Commercial AI systems show variable performance in nodule detection and classification, underscoring the need for users to understand each system's characteristics and interpret results within clinical context.
Authors
- Hsuan-Ming Chang
- Khulan Khurelsukh (ORCID: https://orcid.org/0009-0007-8758-1846)
- Yenpo Lin (ORCID: https://orcid.org/0000-0001-9617-503X)
- Yung-Liang Wan
- Pei-Ching Huang
- Chen-Te Wu
- Wen-Chi Hsu
Institutions
- Chang Gung University (TW)
- Mongolian National University (MN)
- Linkou Chang Gung Memorial Hospital (TW)
Publication Details
- Journal
- Journal of Thoracic Imaging
- Published
- 2026-03-12
- DOI
- https://doi.org/10.1097/rti.0000000000000877
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00