<scp>OncoTrace</scp>‐<scp>TOO</scp>: Interpretable Machine Learning Framework for Cancer Tissue‐of‐Origin Identification Using Transcriptomic Signatures
OncoTrace-TOO not only offers high predictive accuracy for tissue-of-origin classification, but also delivers biologically meaningful insights that support clinical decision-making. This framework holds promise for improving diagnostic precision and guiding personalized treatment in challenging cancer cases.
Authors
- Haochun Huang
- Yang Hao (ORCID: https://orcid.org/0009-0006-9998-6448)
- Xin Liu (ORCID: https://orcid.org/0000-0002-6542-3181)
- Daiyun Huang (ORCID: https://orcid.org/0000-0002-3067-7165)
- Jianwen Ruan
- J. Y. Zhang
Institutions
- Central South University (CN)
- Shanghai Jiao Tong University (CN)
- Haikou City People's Hospital (CN)
- Xi’an Jiaotong-Liverpool University (CN)
Publication Details
- Journal
- Cancer Reports
- Published
- 2025-08-01
- DOI
- https://doi.org/10.1002/cnr2.70311
- Citations
- 1
- Primary Topic
- Cancer Diagnosis and Treatment
- Type
- article
- Field-Weighted Citation Impact
- 1.05