Multi-omics characterization and machine learning of lung adenocarcinoma molecular subtypes to guide precise chemotherapy and immunotherapy
Thorough examination of multi-omics data offers vital understanding and improves the molecular categorization of LUAD. Utilizing a powerful machine learning system, we highlight the immense potential of the riskscore in providing individualized risk evaluations and customized treatment suggestions for LUAD patients.
Authors
- Yuzhi Wang (ORCID: https://orcid.org/0000-0001-7180-2738)
- Haitao Qian (ORCID: https://orcid.org/0000-0003-3934-740X)
- Yi Zhang (ORCID: https://orcid.org/0000-0001-7641-6350)
Institutions
- Deyang Stomatological Hospital (CN)
- The First People’s Hospital of Lianyungang (CN)
- Guang’anmen Hospital (CN)
- Chongqing Medical University (CN)
Publication Details
- Journal
- Frontiers in Immunology
- Published
- 2024-11-28
- DOI
- https://doi.org/10.3389/fimmu.2024.1497300
- Citations
- 5
- Primary Topic
- Ferroptosis and cancer prognosis
- Type
- article
- Field-Weighted Citation Impact
- 2.09