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Results: 25
Number of items: 25
  • Open Access
    Noteboom, S. H. (2026). Data-driven decisions: Optimizing critical care through date integration and predictive decision support. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    Yiasemis, G. (2026). What we do sample, we must learn to reconstruct: From missing k-space data to meaningful images: Deep learning in MRI reconstruction and beyond. [Thesis, externally prepared, Universiteit van Amsterdam].
  • Open Access
    Botros, M., Verheijen, L., de Boer, O. J., Halfwerk, H., Brosens, L. A. A., ten Kate, F. J. C., Ooms, A. H. A. G., Oudijk, L., van der Post, C. R. S., van der Wel, M. J., Bekkers, E. J., Kervadec, H., Sánchez, C. I., & Meijer, S. L. (2026). Detecting aberrant p53 immunohistochemical expression patterns in patients with Barrett’s esophagus using artificial intelligence. Journal of Medical Imaging, 13(1), Article 017503. https://doi.org/10.1117/1.JMI.13.1.017503
  • Płotka, S., Szczepański, T., Szenejko, P. I., Brawura Biskupski Samaha, R., Khalil, A., Rodriguez Calvo, J., Shamshirsaz, A., Isgum, I., Sánchez Gutiérrez, C. I., & Sitek, A. (2025, July 22). Dataset of placental vessel segmentation for Twin-to-Twin Transfusion Syndrome [Data set]. Zenodo. https://doi.org/10.5281/zenodo.16309258
  • Open Access
    Islam, M. M., Anand, R., Wessels, D. R., de Kruiff, F., Kuipers, T. P., Ying, R., Sánchez, C. I., Vadgama, S., Bökman, G., & Bekkers, E. J. (2025). Platonic transformers: A solid choice for equivariance. (v1 ed.) ArXiv. https://doi.org/10.48550/arXiv.2510.03511
  • Open Access
    Płotka, S., Szczepański, T., Szenejko, P., Korzeniowski, P., Rodriguez Calvo, J., Khalil, A., Shamshirsaz, A., Brawura-Biskupski-Samaha, R., Išgum, I., Sánchez, C. I., & Sitek, A. (2025). Real-time placental vessel segmentation in fetoscopic laser surgery for Twin-to-Twin Transfusion Syndrome. Medical Image Analysis, 99, Article 103330. https://doi.org/10.1016/j.media.2024.103330
  • Open Access
    Noteboom, S. H., Kho, E., Galanty, M., Sánchez, C. I., ten Bookum, F. C. P., Veelo, D. P., Vlaar, A. P. J., & van der Ster, B. J. P. (2025). From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision support. eBioMedicine, 111, Article 105529. https://doi.org/10.1016/j.ebiom.2024.105529
  • Open Access
    de Vente, C. W. (2025). Towards robust deep learning for medical imaging: Applications in ophthalmology and radiology. [Thesis, fully internal, Universiteit van Amsterdam].
  • Open Access
    de Vente, C., Valmaggia, P., Hoyng, C. B., Holz, F. G., Islam, M. M., Klaver, C. C. W., Boon, C. J. F., Schmitz-Valckenberg, S., Tufail, A., Saßmannshausen, M., & Sánchez, C. I. (2024). Generalizable Deep Learning for the Detection of Incomplete and Complete Retinal Pigment Epithelium and Outer Retinal Atrophy: A MACUSTAR Report. Translational Vision Science and Technology, 13(9), Article 11. https://doi.org/10.1167/tvst.13.9.11
  • Open Access
    Galanty, M., Luitse, D., Noteboom, S. H., Croon, P., Vlaar, A. P., Poell, T., Sánchez Gutiérrez, C. I., Blanke, T., & Išgum, I. (2024). Assessing the documentation of publicly available medical image and signal datasets and their impact on bias using the BEAMRAD tool. Scientific Reports, 14, Article 31846. https://doi.org/10.1038/s41598-024-83218-5
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