Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer
- DOI
- 10.1007/978-3-031-27420-6_14
- Published
- 2023
- Container
- Lecture Notes in Computer Science
- Publisher
- Springer Nature Switzerland
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1007/978-3-031-27420-6_14,
title = {Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer},
author = {Mingyuan Meng and Lei Bi and Dagan Feng and Jinman Kim},
year = {2023},
journal = {Lecture Notes in Computer Science},
doi = {10.1007/978-3-031-27420-6_14},
url = {https://doi.org/10.1007/978-3-031-27420-6_14}
}RIS
TY - JOUR TI - Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer AU - Mingyuan Meng AU - Lei Bi AU - Dagan Feng AU - Jinman Kim PY - 2023 JO - Lecture Notes in Computer Science DO - 10.1007/978-3-031-27420-6_14 UR - https://doi.org/10.1007/978-3-031-27420-6_14 ER -
APA
Meng, M., Bi, L., Feng, D., & Kim, J. (2023). Radiomics-Enhanced Deep Multi-task Learning for Outcome Prediction in Head and Neck Cancer. Lecture Notes in Computer Science. https://doi.org/10.1007/978-3-031-27420-6_14
Source records
- crossref · retrieved 2026-11-10T12:21:15.399Z