Y. Gao
Recente publicaties
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Han, L., Tan, T., Huang, Y., Dou, H., Zhang, T., Gao, Y., Wang, X., Lu, C., Liang, X., Sun, Y., Teuwen, J., Zhou, S. K., & Mann, R. (2025). All-in-one medical image-to-image translation. Cell Reports Methods, 5(8), Article 101138. https://doi.org/10.1016/j.crmeth.2025.101138Meer informatie over deze publicatie
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Han, L., Zhang, T., D'Angelo, A., van der Voort, A., Pinker-Domenig, K., Kok, M., Sonke, G., Gao, Y., Wang, X., Lu, C., Liang, X., Teuwen, J., Tan, T., & Mann, R. (2025). Exploring personalized neoadjuvant therapy selection strategies in breast cancer: an explainable multi-modal response model. EClinicalMedicine, 86, Article 103356. https://doi.org/10.1016/j.eclinm.2025.103356Meer informatie over deze publicatie
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Rasoolzadeh, N., Zhang, T., Gao, Y., van Dijk, J. M., Yang, Q., Tan, T., & Mann, R. M. (2025). Multimodal Breast MRI Language-Image Pretraining (MLIP): An Exploration of a Breast MRI Foundation Model. In R. M. Mann, T. Zhang, L. Han, G. Litjens, T. Tan, D. Truhn, S. Li, Y. Gao, S. Doyle, R. Martí Marly, J. N. Kather, K. Pinker-Domenig, & S. Wu (Eds.), Artificial Intelligence and Imaging for Diagnostic and Treatment Challenges in Breast Care - 1st Deep Breast Workshop, Deep-Breath 2024, Held in Conjunction with MICCAI 2024, Proceedings (Vol. 15451 LNCS, pp. 42-53). Springer Verlag. https://doi.org/10.1007/978-3-031-77789-9_5Meer informatie over deze publicatie
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Gao, Y., Tan, T., Wang, X., Beets-Tan, R., Zhang, T., Han, L., Portaluri, A., Lu, C., Liang, X., Teuwen, J., Zhou, H. Y., & Mann, R. (2025). Multi-modal Longitudinal Representation Learning for Predicting Neoadjuvant Therapy Response in Breast Cancer Treatment. IEEE Journal of Biomedical and Health Informatics. Advance online publication. https://doi.org/10.1109/JBHI.2025.3540574Meer informatie over deze publicatie
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Gao, Y., Ventura-Diaz, S., Wang, X., He, M., Xu, Z., Weir, A., Zhou, H. Y., Zhang, T., van Duijnhoven, F. H., Han, L., Li, X., D’Angelo, A., Longo, V., Liu, Z., Teuwen, J., Kok, M., Beets-Tan, R., Horlings, H. M., Tan, T., & Mann, R. (2024). An explainable longitudinal multi-modal fusion model for predicting neoadjuvant therapy response in women with breast cancer. Nature Communications, 15(1), Article 9613. https://doi.org/10.1038/s41467-024-53450-8Meer informatie over deze publicatie
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Zhang, T., Tan, T., Han, L., Wang, X., Gao, Y., van Dijk, J., Portaluri, A., Gonzalez-Huete, A., D'Angelo, A., Lu, C., Teuwen, J., Beets-Tan, R., Sun, Y., & Mann, R. (2024). IMPORTANT-Net: Integrated MRI multi-parametric increment fusion generator with attention network for synthesizing absent data. Information Fusion, 108, Article 102381. https://doi.org/10.1016/j.inffus.2024.102381Meer informatie over deze publicatie
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Cao, R., Liu, Y., Wen, X., Liao, C., Wang, X., Gao, Y., & Tan, T. (2024). Reinvestigating the performance of artificial intelligence classification algorithms on COVID-19 X-Ray and CT images. iScience, 27(5), Article 109712. https://doi.org/10.1016/j.isci.2024.109712Meer informatie over deze publicatie
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Han, L., Tan, T., Zhang, T., Huang, Y., Wang, X., Gao, Y., Teuwen, J., & Mann, R. (2024). Synthesis-based imaging-differentiation representation learning for multi-sequence 3D/4D MRI. Medical Image Analysis, 92, Article 103044. https://doi.org/10.1016/j.media.2023.103044Meer informatie over deze publicatie
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Gao, Y., Zhou, H.-Y., Wang, X., Zhang, T., Han, L., Lu, C., Liang, X., Teuwen, J., Beets-Tan, R., Tan, T., Mann, R., Linguraru, MG., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K., & Schnabel, JA. (2024). Improving Neoadjuvant Therapy Response Prediction by Integrating Longitudinal Mammogram Generation with Cross-Modal Radiological Reports: A Vision-Language Alignment-Guided Model. In M. G. Linguraru, A. Feragen, B. Glocker, J. A. Schnabel, Q. Dou, S. Giannarou, & K. Lekadir (Eds.), MEDICAL IMAGE COMPUTING AND COMPUTER ASSISTED INTERVENTION: MICCAI 2024, PT I (Vol. 15001, pp. 133-143). Springer. https://doi.org/10.1007/978-3-031-72378-0_13Meer informatie over deze publicatie
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Han, L., Tan, T., Zhang, T., Wang, X., Gao, Y., Lu, C., Liang, X., Dou, H., Huang, Y., Mann, R., Linguraru, MG., Dou, Q., Feragen, A., Giannarou, S., Glocker, B., Lekadir, K., & Schnabel, JA. (2024). Non-adversarial Learning: Vector-Quantized Common Latent Space for Multi-sequence MRI. In M. G. Linguraru, A. Feragen, B. Glocker, J. A. Schnabel, Q. Dou, S. Giannarou, & K. Lekadir (Eds.), Medical Image Computing and Computer Assisted Intervention - MICCAI 2024 - 27th International Conference, Proceedings: MICCAI 2024, PT XI (Vol. 15011, pp. 481-491). Springer. https://doi.org/10.1007/978-3-031-72120-5_45Meer informatie over deze publicatie