Predicting Overall Survival of NSCLC Patients with Clinical, Radiomics and Deep Learning Features.
- DOI
- 10.1007/s10278-025-01828-5
- Published
- 2026 Jan 13
- Container
- Journal of imaging informatics in medicine
- Publisher
- Not recorded
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/s10278-025-01828-5,
title = {Predicting Overall Survival of NSCLC Patients with Clinical, Radiomics and Deep Learning Features.},
author = {Kanakarajan H and Zhou J and Gomes AL and Kalendralis P and Liang W and Tohidinezhad F and Dekker A and De Baene W and Sitskoorn M},
year = {2026},
journal = {Journal of imaging informatics in medicine},
doi = {10.1007/s10278-025-01828-5},
url = {https://doi.org/10.1007/s10278-025-01828-5}
}RIS
TY - JOUR TI - Predicting Overall Survival of NSCLC Patients with Clinical, Radiomics and Deep Learning Features. AU - Kanakarajan H AU - Zhou J AU - Gomes AL AU - Kalendralis P AU - Liang W AU - Tohidinezhad F AU - Dekker A AU - De Baene W AU - Sitskoorn M PY - 2026 JO - Journal of imaging informatics in medicine DO - 10.1007/s10278-025-01828-5 UR - https://doi.org/10.1007/s10278-025-01828-5 ER -
APA
H, K., J, Z., AL, G., P, K., W, L., F, T., A, D., W, D. B., & M, S. (2026). Predicting Overall Survival of NSCLC Patients with Clinical, Radiomics and Deep Learning Features.. Journal of imaging informatics in medicine. https://doi.org/10.1007/s10278-025-01828-5
Source records
- pubmed · retrieved 2026-09-25T19:28:23.345Z