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Results: 3
Number of items: 3
  • Open Access
    Wiers, J., Wessels, D., Alvarez-Florez, L., Bujalance Gomez, A., Ruiperez-Campillo, S., Kolk, M., Bekkers, E., & Tjong, F. (2026). Enhancing stability in cardiac risk stratification with equivariant neural fields. European Heart Journal - Digital Health, 7(Supplement 1), Article ztaf143.052. https://doi.org/10.1093/ehjdh/ztaf143.052
  • Open Access
    Alvarez-Florez, L., Sander, J., Bourfiss, M., Tjong, F. V. Y., Velthuis, B. K., & Išgum, I. (2024). Deep Learning for Automatic Strain Quantification in Arrhythmogenic Right Ventricular Cardiomyopathy. In O. Camara, E. Puyol-Antón, M. Sermesant, A. Suinesiaputra, Q. Tao, C. Wang, & A. Young (Eds.), Statistical Atlases and Computational Models of the Heart: Regular and CMRxRecon Challenge Papers: 14th International Workshop, STACOM 2023, held in conjunction with MICCAI 2023, Vancouver, BC, Canada, October 12, 2023 : revised selected papers (pp. 25–34). (Lecture Notes in Computer Science; Vol. 14507). Springer. https://doi.org/10.1007/978-3-031-52448-6_3
  • Open Access
    Kolk, M. Z. H., Ruipérez-Campillo, S., Allaart, C. P., Wilde, A. A. M., Knops, R. E., Narayan, S. M., Tjong, F. V. Y., & DEEP RISK investigators (2024). Multimodal explainable artificial intelligence identifies patients with non-ischaemic cardiomyopathy at risk of lethal ventricular arrhythmias. Scientific Reports, 14, Article 14889. https://doi.org/10.1038/s41598-024-65357-x
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