PRIME: an interpretable artificial intelligence model based on liquid biopsy improves prediction of progression risk in non-small cell lung cancer
As an interpretable model integrating readily-accessible and crucial clinical-genomic predictors, PRIME achieves enhanced performance, allowing for early outcome prediction, refined risk stratification, and personalized clinical decision-making.
Authors
- N Bi
- Wen-yang Liu
- Xiang Yongbo
- Lu-hua Wang
- S. Gao
- L. Deng
- Yu Wang
- Tao Zhang
- Xiao-Wei Chen
- Jian-Yang Wang
Institutions
- Chinese Academy of Medical Sciences & Peking Union Medical College (CN)
- National Cancer Center (US)
Publication Details
- Journal
- Military Medical Research
- Published
- 2026-01-06
- DOI
- https://doi.org/10.1186/s40779-025-00679-z
- Primary Topic
- Cancer Genomics and Diagnostics
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Peking Union Medical College
- Bijzonder Onderzoeksfonds UGent