Andre Dekker (A.L.A.J.)

Li, W., Pan, X., Zhang, Z., Wu, G., Ye, G., Wee, L., Dekker, A., Han, C., Shi, L., Liu, Z., Liu, Z., & Shi, Z. (2025). Data-efficient federated semi-supervised learning framework via pseudo supervision refinement strategy for lung tumor segmentation. Biomedical Signal Processing and Control, 107, Article 107793. https://doi.org/10.1016/j.bspc.2025.107793

Liu, Z., Li, W., Cui, Y., Chen, X., Pan, X., Ye, G., Wu, G., Liao, Y., Volmer, L., Wee, L., Dekker, A., Han, C., Liu, Z., & Shi, Z. (2025). Label-efficient transformer-based framework with self-supervised strategies for heterogeneous lung tumor segmentation. Expert Systems with Applications, 269, Article 126364. https://doi.org/10.1016/j.eswa.2024.126364

Zhang, Z., Luo, T., Yan, M., Shen, H., Tao, K., Zeng, J., Yuan, J., Fang, M., Zheng, J., Bermejo, I., Dekker, A., Ruysscher, D. D., Wee, L., Zhang, W., Jiang, Y., & Ji, Y. (2025). Voxel-level radiomics and deep learning for predicting pathologic complete response in esophageal squamous cell carcinoma after neoadjuvant immunotherapy and chemotherapy. Journal for ImmunoTherapy of Cancer, 13(3), Article e011149. https://doi.org/10.1136/jitc-2024-011149

Oomens, J. E., Moonen, J. E. F., Vos, S. J. B., Beran, M., Mateus, P., De Deyn, P. P., van der Flier, W. M., Geerlings, M. I., Huisman, M. A., Ikram, M. A., Schram, M. T., Slagboom, P. E., Verschuren, W. M. M., Beekman, M., Bermejo, I., Birhanu, M., Bron, E. E., Dekker, A., Frentz, I., ... Visser, P. J. (2025). Identifying pathways to the prevention of dementia: the Netherlands consortium of dementia cohorts. BMC Neurology, 25(1), Article 59. https://doi.org/10.1186/s12883-024-03995-4

Puts, S., Zegers, C. M. L., Dekker, A., & Bermejo, I. (2025). Developing an ICD-10 Coding Assistant: Pilot Study Using RoBERTa and GPT-4 for Term Extraction and Description-Based Code Selection. JMIR Formative Research, 9, Article e60095. https://doi.org/10.2196/60095

Rattay, T., Verhoeven, K., Bergeaud, M., Bologna, G., Cortellessa, G., Dekker, A., Fracasso, F., Joore, M., Koutsopoulos, I., Liang, Y., Panisson, A., Perotti, A., Ramaekers, B., Roumen, C., van Soest, J., Stobart, H., Talbot, C. J., Webb, A. J., Rivera, S., & PRE-ACT Study Consortium (2025). PRE-ACT-01: The Prediction of Radiotherapy side Effects using explainable AI for patient Communication and Treatment modification-01 Trial. Breast, 80, Article 104247. https://doi.org/10.1016/j.breast.2025.104247

Price, G., Peek, N., Eleftheriou, I., Spencer, K., Paley, L., Hogenboom, J., van Soest, J., Dekker, A., van Herk, M., & Faivre-Finn, C. (2025). An Overview of Real-World Data Infrastructure for Cancer Research. Clinical Oncology, 38, Article 103545. https://doi.org/10.1016/j.clon.2024.03.011

Choudhury, A., Volmer, L., Martin, F., Fijten, R., Wee, L., Dekker, A., & van Soest, J. (2025). Advancing Privacy-Preserving Health Care Analytics and Implementation of the Personal Health Train: Federated Deep Learning Study. JMIR AI, 4, Article e60847. https://doi.org/10.2196/60847

Yan, M., Zhang, Z., Tian, J., Yu, J., Dekker, A., De Ruysscher, D., Wee, L., & Zhao, L. (2025). Whole lung radiomic features are associated with overall survival in patients with locally advanced non-small cell lung cancer treated with definitive radiotherapy. Radiation Oncology, 20(1), Article 9. Advance online publication. https://doi.org/10.1186/s13014-025-02583-1

Chen, X., Huang, Y., Wee, L., Zhao, K., Mao, Y., Li, Z., Yao, S., Li, S., Liang, Y., Huang, X., Dekker, A., Chen, X., & Liu, Z. (2024). Integrated analysis of radiomics, RNA, and clinicopathologic phenotype reveals biological basis of prognostic risk stratification in colorectal cancer. Science Bulletin, 69(23), 3666-3671. https://doi.org/10.1016/j.scib.2024.10.005