Pathomics-based machine learning models for optimizing LungPro navigational bronchoscopy in peripheral lung lesion diagnosis: a retrospective study
The fusion diagnostic model that incorporates clinical and pathomic features markedly enhances the diagnostic accuracy of LungPro in this retrospective cohort. This model aids in the detection of subtle malignant characteristics, thereby offering evidence to support precise and targeted therapeutic interventions for lesions that LungPro classifies as negative in clinical settings.
Authors
- Yiwen Tan
- Ying-Cun Bao (ORCID: https://orcid.org/0000-0003-1299-2177)
- Shengjin Li (ORCID: https://orcid.org/0000-0003-1044-3262)
- Feng Ying
- Xiaoyu Ma (ORCID: https://orcid.org/0009-0000-6183-2175)
Institutions
- Dalian Medical University (CN)
- Second Affiliated Hospital of Chongqing Medical University (CN)
- Union Hospital (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- BioMedical Engineering OnLine
- Published
- 2025-09-26
- DOI
- https://doi.org/10.1186/s12938-025-01440-2
- Primary Topic
- Lung Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Chongqing Medical University
- Centre Scientifique et Technique du Bâtiment