Open Access
| Issue |
ITM Web Conf.
Volume 85, 2026
Intelligent Systems for a Sustainable Future (ISSF 2026)
|
|
|---|---|---|
| Article Number | 01009 | |
| Number of page(s) | 6 | |
| Section | AI for Healthcare, Agriculture, Smart Society & Computer Vision | |
| DOI | https://doi.org/10.1051/itmconf/20268501009 | |
| Published online | 09 April 2026 | |
- R. Zeleznik et al., "Deep convolutional neural networks to predict cardiovascular risk from computed tomography," Nature Communications, vol. 12, no. 1, 2021. [Google Scholar]
- S. G. M. van Velzen et al., "Deep learning for automatic calcium scoring in CT: Validation across multiple institutions," European Radiology, vol. 30, no. 8, pp. 1–10, 2020. [Google Scholar]
- Cano-Espinosa et al., "Explainable AI for coronary artery calcium scoring: Clinical validation of attention maps," IEEE Transactions on Medical Imaging, 2022. [Google Scholar]
- J. Sandhu et al., "Multi-ethnic validation of a deep learning system for coronary artery calcium scoring in non-gated CT," Radiology: Artificial Intelligence, 2023. [Google Scholar]
- M. Naghavi et al., "Artificial intelligence applied to coronary artery calcium scans improves prediction of cardiovascular events," NPJ Digital Medicine, vol. 7, 2024. [Google Scholar]
- T. Takahashi et al., "Fully automated AI model for coronary artery calcium quantification on ECG-gated CT," European Heart Journal - Digital Health, 2023. [Google Scholar]
- F. Föllmer et al., "Automated segment-level coronary artery calcium scoring on non-contrast CT," Medical Physics, 2024. [Google Scholar]
- X. Wang et al., "Meta-analysis of deep learning methods for automatic coronary artery calcium scoring," Computerized Medical Imaging and Graphics, 2024. [Google Scholar]
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