L.Y.L. Wee

Zhou, M., Li, M., Cao, Q., Zhang, Z., Wee, L., Dekker, A., Zhu, J., Jiang, H., Jiang, J., Miao, X., Mao, W., Yan, M., & Lu, H. (2026). Malignant pleural mesothelioma classification and survival prediction with CT imaging using ResNet. European Radiology, 36(4), 2603-2614. https://doi.org/10.1007/s00330-025-12094-y

Chen, S., Liu, Z., Wang, J., Zhang, Z., Dekker, A., Wee, L., Kalendralis, P., Sun, Y., & Tong, T. (2026). Correction: Automatically quantifying spatial heterogeneity of immune and tumor hypoxia environment and predicting disease-free survival for patients with rectal cancer (vol 74 , 380 , 2025). Cancer Immunology Immunotherapy, 75(4), Article 113. https://doi.org/10.1007/s00262-026-04315-0

Wang, J., Jiang, Z., Ji, W., Cheng, H., Zhang, Z., Dekker, A., Wee, L., Yan, M., & Lai, X. (2026). Cross-dataset adaptation of voxel-level deep radiomics for predicting survival in inoperable locally advanced NSCLC treated with immunotherapy. Frontiers in Immunology, 17, Article 1787518. https://doi.org/10.3389/fimmu.2026.1787518

Huang, Y., Wei, Z., Ye, G., Cui, Y., Li, C., Wu, G., Yang, W., Zhang, B., Zhang, Z., Jiang, Y., Hendriks, L. E. L., Wee, L., De Ruysscher, D., Dekker, A., Shi, L., Liu, Z., He, B., & Shi, Z. (2026). Automated CT-derived body composition predicts pathologic response to neoadjuvant immunotherapy in non–small cell lung cancer. Cancer Letters, 640, Article 218229. https://doi.org/10.1016/j.canlet.2025.218229

van Daalen, F., Sasidharan, B. K., Praveenraj, C., Varghese, A. J., Dekker, A., Wee, L., Fijten, R., Irodi, A., & Thomas, H. M. T. (2026). Decoding Uncertainty Quantification for Oncology-An Illustration Using Radiomics. Diagnostics, 16(5), Article 700. https://doi.org/10.3390/diagnostics16050700

Hogenboom, J., Gouthamchand, V., Cairns, C., Janssen, S. H. M., Way, K., Dekker, A. L. A. J., van der Graaf, W. T. A., Darlington, A.-S., Husson, O., Wee, L. Y. L., van Soest, J., & Lobo Gomes, A. (2026). Knowledge Representation of a Multicenter Adolescent and Young Adult Cancer Infrastructure: Development of the STRONG AYA Knowledge Graph. JCO Clinical Cancer Informatics, 10, Article e2500177. https://doi.org/10.1200/CCI-25-00177

Gu, Q., Chen, S., Dekker, A., Wee, L., Kalendralis, P., Yan, M., Wang, J., Yuan, J., & Jiang, Y. (2026). Variational autoencoder-based deep learning and radiomics for predicting pathologic complete response to neoadjuvant chemoimmunotherapy in locally advanced oesophageal squamous cell carcinoma. British Journal of Radiology, 99(1177), 133-142. https://doi.org/10.1093/bjr/tqaf239

Hu, E., Qiu, P., Dekker, A., Wee, L., Quan, C., Zhang, D., Liang, W., & Xie, N. (2026). CCR5 expression and conformational stability as potential cooperative modulators of immune phenotypes and therapy response in breast cancer. Discover. Oncology, 17(1), Article 31. https://doi.org/10.1007/s12672-025-04189-1

Qi, B., Jiang, Z., Shen, H., Li, J., Wang, Z., Fang, M., Wang, C., Jiang, Y., Yuan, J., Bermejo, I., Dekker, A., De Ruysscher, D., Wee, L., Zhang, W., Ji, Y., & Zhang, Z. (2025). Interpretable multimodal radiopathomics model predicting pathological complete response to neoadjuvant chemoimmunotherapy in esophageal squamous cell carcinoma. Journal for ImmunoTherapy of Cancer, 13(12), Article e013840. https://doi.org/10.1136/jitc-2025-013840

Yu, L., Chen, S., Li, J., Yi, H. Q., Wang, J., Ni, J., Zheng, X., Ge, H., Zhu, Z., Xing, L., Kalendralis, P., Wee, L., Dekker, A., Zhang, Z., Ye, Z., & Yuan, Z. (2025). PET/CT-based deep learning model predicts distant metastasis after SBRT for early-stage NSCLC: A multicenter study. Computerized Medical Imaging and Graphics, 126, Article 102663. https://doi.org/10.1016/j.compmedimag.2025.102663