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Ontdekken: Context-Aware Deep Learning for Biomedical Time Series AnalysisVasculAIContext-Aware Deep Learning for Biomedical Time Series Analysis
Paper Fonteyn, Karel. Context-Aware Deep Learning for Biomedical Time Series Analysis. Ghent University. Faculty of Engineering and Architecture, 2026. (https://biblio.ugent.be/publication/01KKKB78QC0R4W7WT8EACMPA9P) Documents 16 March 2026 – UGent
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Ontdekken: CSD-AFNet : computationally efficient atrial fibrillation classification from ECGs using 2D causal strided dilated convolutionsVasculAICSD-AFNet : computationally efficient atrial fibrillation classification from ECGs using 2D causal strided dilated convolutions
Paper L. Bontinck, A. Steyaert, H. Chen, T. Dhaene, and D. Deschrijver, “CSD-AFNet : computationally efficient atrial fibrillation classification from ECGs using 2D causal strided dilated convolutions,” in 2025 IEEE EMBS International Conference on Biomedical and Health Informatics (BHI), Atlanta,…
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Ontdekken: Comprehensive Analysis of Hybrid Approaches to Li-Fi and LPWAN Systems for IoT with Satellite-Assisted CommunicationVasculAIComprehensive Analysis of Hybrid Approaches to Li-Fi and LPWAN Systems for IoT with Satellite-Assisted Communication
Paper Adi, P. D. P. et al. (2025). Comprehensive Analysis of Hybrid Approaches to Li-Fi and LPWAN Systems for IoT with Satellite-Assisted Communication. IETE Technical Review, 42(5), 597-631, doi.org/10.1080/02564602.2025.2560812 Documents 29 September 2025 – UPHF
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Ontdekken: Augmentation-Free Longitudinal Modeling Through Structuring Whitened EmbeddingsVasculAIAugmentation-Free Longitudinal Modeling Through Structuring Whitened Embeddings
Paper Fonteyn, K., Bontinck, L., Dhaene, T., & Deschrijver, D. (2025). Augmentation-Free Longitudinal Modeling Through Structuring Whitened Embeddings. IEEE Access. Documents 11 September 2025 – UGent
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Ontdekken: Mid-term benefits and short-term haemodynamic evaluation by kinocardiography of left bundle branch pacing compared with apical ventricular pacingVasculAIMid-term benefits and short-term haemodynamic evaluation by kinocardiography of left bundle branch pacing compared with apical ventricular pacing
Paper Godart, D., Godart, P., Lemaitre, J., Therasse, A., Migeotte, P. F., Rozen, L., Collet, A., & Carlier, S. (2025). Mid-term benefits and short-term haemodynamic evaluation by kinocardiography of left bundle branch pacing compared with apical ventricular pacing. European Heart…
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Ontdekken: Revolutionizing vascular monitoring (“Researchers’ Tuesday”)VasculAIRevolutionizing vascular monitoring (“Researchers’ Tuesday”)
Poster Kevin Stekelorom, Puput Dani Prasetyo Adi, Karim Dogheche, Nasrullah Armi, Iyad Dayoub, El Hadj Dogheche.. Revolutionizing vascular monitoring. Mardi des chercheurs 2025, Apr 2025, Valenciennes, France. Documents 1st April 2025 – UPHF“Researchers’ Tuesday 2025”
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Ontdekken: Revolutionizing vascular monitoring – “Franco-indonesian workshop”VasculAIRevolutionizing vascular monitoring – “Franco-indonesian workshop”
Poster Kevin Stekelorom, Puput Dani Prasetyo Adi, Karim Dogheche, Nasrullah Armi, Iyad Dayoub, El Hadj Dogheche.. “Revolutionizing vascular monitoring.” Workshop BRIN-UPHF Decembre 2024 Documents 15 December 2024 – UPHF1st Franco-indonesian cooperation workshop
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Ontdekken: Improvement of LR-FHSS LPWAN Satellite Communication for IoMTVasculAIImprovement of LR-FHSS LPWAN Satellite Communication for IoMT
Paper P. D. Prasetyo Adi, E. Dogheche, I. Dayoub, K. Stekelorom, D. Remiens, N. Armi, “Improvement of LR-FHSS LPWAN Satellite Communication for IoMT,” 2024 7th International Seminar on Research of Information Technology and Intelligent Systems (ISRITI), Yogyakarta, Indonesia, 2024, pp.…
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Ontdekken: ECGencode: Compact and Computationally Efficient Deep Learning Feature Encoder for ECG SignalsVasculAIECGencode: Compact and Computationally Efficient Deep Learning Feature Encoder for ECG Signals
Paper L. Bontinck et al., « ECGencode: Compact and Computationally Efficient Deep Learning Feature Encoder for ECG Signals », Expert Systems with Applications. DOI: 10.1016/j.eswa.2024.124775 Documents 1 December 2024 – UGent
