Multiomics-Based Deep Learning Prediction of Prognosis and Therapeutic Response in Patients With Extensive-Stage Small Cell Lung Cancer Receiving Chemoimmunotherapy: A Retrospective Cohort Study
We developed prediction model based on multi-omics demonstrated satisfactory performance in predicting chemoimmunotherapy response in patients with ES-SCLC. The random forest prediction model, in particular, provides accurate response and prognostic risk assessments, thereby assisting clinical decision-making.
Authors
- Jiahui Du (ORCID: https://orcid.org/0000-0003-3238-0469)
- Xiufeng Pei
- Feng Lu (ORCID: https://orcid.org/0000-0003-3933-8490)
- Jian‐Ying Wang (ORCID: https://orcid.org/0000-0003-3002-1040)
- Yonggang Liu
- Wanting Shi (ORCID: https://orcid.org/0000-0002-0209-0930)
- Fang Nie (ORCID: https://orcid.org/0009-0000-5890-1053)
Institutions
- Inner Mongolia University of Science and Technology (CN)
- Baotou Central Hospital (CN)
- Baotou Medical College (CN)
Publication Details
- Journal
- International Journal of General Medicine
- Published
- 2025-02-01
- DOI
- https://doi.org/10.2147/ijgm.s506485
- Citations
- 1
- Primary Topic
- Lung Cancer Research Studies
- Type
- article
- Field-Weighted Citation Impact
- 1.05