L.Y.L. Wee

Uitgebreid profiel is alleen beschikbaar in Engels.

Gottardelli, B., Gouthamchand, V., Masciocchi, C., Boldrini, L., Martino, A., Mazzarella, C., Massaccesi, M., Monshouwer, R., Findhammer, J., Wee, L., Dekker, A., Gambacorta, M. A., & Damiani, A. (2024). A distributed feature selection pipeline for survival analysis using radiomics in non-small cell lung cancer patients. Scientific Reports, 14(1), Article 7814. https://doi.org/10.1038/s41598-024-58241-1
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Yu, L., Zhang, Z., Yi, H. Q., Wang, J., Li, J., Wang, X., Bai, H., Ge, H., Zheng, X., Ni, J., Qi, H., Guan, Y., Xu, W., Zhu, Z., Xing, L., Dekker, A., Wee, L., Traverso, A., Ye, Z., & Yuan, Z. (2024). A PET/CT radiomics model for predicting distant metastasis in early-stage non-small cell lung cancer patients treated with stereotactic body radiotherapy: a multicentric study. Radiation Oncology, 19(1), Article 10. https://doi.org/10.1186/s13014-024-02402-z
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Shanley, D., Hogenboom, J., Lysen, F., Wee, L., Lobo Gomes, A., Dekker, A., & Meacham, D. (2024). Getting real about synthetic data ethics: Are AI ethics principles a good starting point for synthetic data ethics? Embo Reports. https://doi.org/10.1038/s44319-024-00101-0
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Zhao, Z., Du, S., Xu, Z., Yin, Z., Huang, X., Huang, X., Wong, C., Liang, Y., Shen, J., Wu, J., Qu, J., Zhang, L., Cui, Y., Wang, Y., Wee, L., Dekker, A., Han, C., Liu, Z., Shi, Z., & Liang, C. (2024). SwinHR: Hemodynamic-powered hierarchical vision transformer for breast tumor segmentation. Computers in biology and medicine, 169, Article 107939. https://doi.org/10.1016/j.compbiomed.2024.107939
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Kulkarni, C., Sherkhane, U., Jaiswar, V., Mithun, S., Mysore Siddu, D., Rangarajan, V., Dekker, A., Traverso, A., Jha, A., & Wee, L. (2023). Comparing the performance of a deep learning-based lung gross tumour volume segmentation algorithm before and after transfer learning in a new hospital. BJR Open, 6(1), Article tzad008. https://doi.org/10.1093/bjro/tzad008
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Jha, A. K., Sherkhane, U. B., Mthun, S., Jaiswar, V., Purandare, N., Prabhash, K., Wee, L., Rangarajan, V., & Dekker, A. (2023). External Validation of Robust Radiomic Signature to Predict 2-Year Overall Survival in Non-Small-Cell Lung Cancer. Journal of Digital Imaging, 36(6), 2519-2531. https://doi.org/10.1007/s10278-023-00835-8
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Mateus, P., Volmer, L., Wee, L., Aerts, H. J. W. L., Hoebers, F., Dekker, A., & Bermejo, I. (2023). Image based prognosis in head and neck cancer using convolutional neural networks: a case study in reproducibility and optimization. Scientific Reports, 13(1), Article 18176. https://doi.org/10.1038/s41598-023-45486-5
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Jha, A. K., Mithun, S., Sherkhane, U. B., Dwivedi, P., Puts, S., Osong, B., Traverso, A., Purandare, N., Wee, L., Rangarajan, V., & Dekker, A. (2023). Emerging role of quantitative imaging (radiomics) and artificial intelligence in precision oncology. Exploration of Targeted Anti-tumor Therapy, 4(4), 569-582. https://doi.org/10.37349/etat.2023.00153
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van der Kroft, G., Wee, L., Rensen, S. S., Brecheisen, R., van Dijk, D. P. J., Eickhoff, R., Roeth, A. A., Ulmer, F. T., Dekker, A., Neumann, U. P., & Olde Damink, S. W. M. (2023). Identifying radiomics signatures in body composition imaging for the prediction of outcome following pancreatic cancer resection. Frontiers in Oncology, 13(1), Article 1062937. https://doi.org/10.3389/fonc.2023.1062937
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Zhang, Y., Wang, Z., Zhang, Z., Liu, J., Feng, Y., Wee, L., Dekker, A., Chen, Q., & Traverso, A. (2023). GAN-based one dimensional medical data augmentation. Soft Computing, 27(15), 10481-10491. https://doi.org/10.1007/s00500-023-08345-z
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L.Y.L. Wee

Researcher

Clinical Data Science

Radiotherapie

GROW, School for Oncology & Reproduction

Fac. Health, Medicine and Life Sciences

leonard.wee@maastro.nl

Zoekterm

L.Y.L. Wee

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L.Y.L. Wee