Development and validation of machine learning-based models for identifying synchronous distant metastasis at initial diagnosis in cutaneous melanoma using the SEER database
- DOI
- 10.21037/tcr-2026-1189
- Published
- 2026-10
- Container
- Translational Cancer Research
- Publisher
- AME Publishing Company
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.21037/tcr-2026-1189,
title = {Development and validation of machine learning-based models for identifying synchronous distant metastasis at initial diagnosis in cutaneous melanoma using the SEER database},
author = {Heng Wang and Jiangfeng Li and Fuguang Zhang and Yuelu Yang and Jianwu Chen and Guangtao Huang},
year = {2026},
journal = {Translational Cancer Research},
doi = {10.21037/tcr-2026-1189},
url = {https://doi.org/10.21037/tcr-2026-1189}
}RIS
TY - JOUR TI - Development and validation of machine learning-based models for identifying synchronous distant metastasis at initial diagnosis in cutaneous melanoma using the SEER database AU - Heng Wang AU - Jiangfeng Li AU - Fuguang Zhang AU - Yuelu Yang AU - Jianwu Chen AU - Guangtao Huang PY - 2026 JO - Translational Cancer Research DO - 10.21037/tcr-2026-1189 UR - https://doi.org/10.21037/tcr-2026-1189 ER -
APA
Wang, H., Li, J., Zhang, F., Yang, Y., Chen, J., & Huang, G. (2026). Development and validation of machine learning-based models for identifying synchronous distant metastasis at initial diagnosis in cutaneous melanoma using the SEER database. Translational Cancer Research. https://doi.org/10.21037/tcr-2026-1189
Source records
- crossref · retrieved 2026-11-09T20:20:11.519Z