Stacked random forest model for colorectal cancer detection using complete blood counts
CBC testing, combined with electronic medical record data, is a low-cost and widely accessible tool. Our robust CRC risk prediction model can serve as a preliminary screening method, aiding in colonoscopy referral decisions and improving CRC screening efficiency.
Authors
- Weiwei Tan (ORCID: https://orcid.org/0000-0001-8915-1152)
- Lingling Kang
- Yijing Chen (ORCID: https://orcid.org/0009-0006-4091-8512)
- Tingji Sun
- Peng Xiao (ORCID: https://orcid.org/0000-0003-0075-581X)
- Junfeng Luo (ORCID: https://orcid.org/0000-0002-9534-2462)
- Hou‐De Zhang (ORCID: https://orcid.org/0000-0001-8680-0073)
- Xiaojuan Jing
- Ya Fu
- Qingyun Li (ORCID: https://orcid.org/0000-0002-6814-8322)
- Xiaozhi Wang (ORCID: https://orcid.org/0000-0002-9829-9332)
- Shaobo Chen (ORCID: https://orcid.org/0009-0005-5710-7284)
- Zhenjun Ma
- Song Xue (ORCID: https://orcid.org/0000-0002-8533-0636)
Institutions
- Sun Yat-sen University (CN)
- Guangdong Medical College (CN)
- Suizhou Central Hospital (CN)
- Sun Yat-sen Memorial Hospital (CN)
- Shanghai University of Traditional Chinese Medicine (CN)
- ShenZhen People’s Hospital (CN)
- Shenzhen Bao'an District People's Hospital (CN)
- Shantou Central Hospital (CN)
- University of Hong Kong - Shenzhen Hospital (CN)
- Shuguang Hospital (CN)
- Anshan Hospital (CN)
- Zhejiang University (CN)
- University of Hong Kong (HK)
Publication Details
- Journal
- Digital Health
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1177/20552076251362072
- Citations
- 1
- Primary Topic
- Inflammatory Biomarkers in Disease Prognosis
- Type
- article
- Field-Weighted Citation Impact
- 1.05