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Y. Chen

Recent publications
  • Chen, Y., Pasquier, D., Verstappen, D., Woodruff, H. C., & Lambin, P. (2025). An interpretable ensemble model combining handcrafted radiomics and deep learning for predicting the overall survival of hepatocellular carcinoma patients after stereotactic body radiation therapy. Journal of Cancer Research and Clinical Oncology, 151(2), Article 84. https://doi.org/10.1007/s00432-025-06119-8
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  • Verstappen, D., Pasquier, D., Chen, Y., Lambin, P., & Woodruff, H. C. (2024). Radiomic feature robustness in CT scans affected by fiducial marker induced streak artifacts for patients with hepatocellular carcinoma. Medical Physics, 51(11), 8362-8370. https://doi.org/10.1002/mp.17329
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  • Zhong, X., Salahuddin, Z., Chen, Y., Woodruff, H. C., Long, H., Peng, J., Xie, X., Lin, M., & Lambin, P. (2023). An Interpretable Radiomics Model Based on Two-Dimensional Shear Wave Elastography for Predicting Symptomatic Post-Hepatectomy Liver Failure in Patients with Hepatocellular Carcinoma. Cancers, 15(21), Article 5303. https://doi.org/10.3390/cancers15215303
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  • Salahuddin, Z., Chen, Y., Zhong, X., Woodruff, H. C., Rad, N. M., Mali, S. A., & Lambin, P. (2023). From Head and Neck Tumour and Lymph Node Segmentation to Survival Prediction on PET/CT: An End-to-End Framework Featuring Uncertainty, Fairness, and Multi-Region Multi-Modal Radiomics. Cancers, 15(7), Article 1932. https://doi.org/10.3390/cancers15071932
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  • Salahuddin, Z., Chen, Y., Zhong, X., Rad, N. M., Woodruff, H. C., & Lambin, P. (2023). HNT-AI: An Automatic Segmentation Framework for Head and Neck Primary Tumors and Lymph Nodes in FDG- PET/CT Images. In V. Andrearczyk, V. Oreiller, A. Depeursinge, & M. Hatt (Eds.), Head and Neck Tumor Segmentation and Outcome Prediction: 3rd Challenge, HECKTOR 2022, Held in Conjunction with MICCAI 2022, Proceedings (3 ed., Vol. 13626 LNCS, pp. 212-220). Springer Verlag. https://doi.org/10.1007/978-3-031-27420-6_21
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