Publikationen

ESC Digital & AI Summit 202612.–13. Nov. 2026Demnächst

1. Deep learning based automatic temporally aligned atrial strain from four chamber cine cardiac MRI

   Müller, S. K., Fischer, S., Kiekenap, J., Koehler, S., Andre, F., Hussain, T., … Engelhardt, S.

2. An LLM-native wiki knowledge graph for HFpEF: structured, traceable clinical question answering in a complex cardiovascular syndrome

   Müller, S. K., Seyfarth, M., Kiekenap, J., Fischer, S., Zeid, S., Wild, P. S., Frey, N., Engelhardt, S.

3. AI-agent-driven autonomous research loop for cardiac MRI deep learning model optimization

   Seyfarth, M., Dar, S. U., Engelhardt, S.

4. Replacing the people who promised to replace clinicians: autonomous AI-agents for cardiac MRI segmentation

   Seyfarth, M., Engelhardt, S., Dar, S.

5. Deep learning-based carotid ultrasound analysis identifies molecular mechanisms of accelerated vascular aging

   ten Cate, V., Gul, G., Balada, C. P., Romano Martinez, A., Zeid, S., Dengel, A., Lurz, P., Wild, P. S.

6. Assessment of physical activity in HFpEF: comparing digital mobility outcomes, cardiopulmonary exercise test and six-minute walk test

   Kerber, A., Zeid, S., Chalabi, J., Söhne, J., Velmeden, D., Fooß, B., … Wild, P. S.

7. Real-world performance of an A4C deep-learning algorithm for detection of cardiac amyloidosis in echocardiography

   Leverenz, J., Reich, C., Roßkopf, S., aus dem Siepen, F., Nagel, C., Hund, H., … Meder, B.

8. Putting ECG foundation models to real-world data test: a prognostic prediction of major adverse cardiovascular events

   Moderierte PosterpräsentationHegde, S., Prüser, M., Merzweiler, A., Heuschmann, P., Dieterich, C.

9. Federated GWAS enables privacy-preserving multi-center genomic analysis – the DZHK cardiovascular cohort as show case

   PosterSergei, G., Dieterich, C., Akgun, M., Swaminathan, A.

Benzon AI Symposium 2026, Kopenhagen7.–10. Sep. 2026

1. Mapping seven decades of cardiomyopathy: a transformer-based analysis of 151,109 publications

   Reich, C., Dönmez Yalcin, G., Sedaghat-Hamedani, F., Amr, A., Frey, N., Meder, B.

ESC Congress 2026

1. A plasma metabolite profile predicts worsening of heart failure and reflects distinct inflammatory mechanisms in symptomatic heart failure

   Yapıcı, E., Zeid, S., Martens, R., Nguyen, S., Koeck, T., ten Cate, V., Schmidlin, T., Wild, P. S.

2. DNA methylation patterns predict primary myocardial infarction

   Ingold, M., Müller, C., Krolevets, M., Yapici, E., Rapp, S., Pfeiffer, N., … Wild, P. S.

ESSB Conference 2026

1. Spatial organization of T cell populations in NSCLC brain metastases

   PosterChazotte, M., Pilger, L.-M., Schniederjohann, C., Dietrich, S., Seiffert, M., Schapiro, D.

ESC Digital & AI Summit 2025, Berlin21.–22. Nov. 2025

Die Abstracts wurden im European Heart Journal – Digital Health, Band 7, Supplement (2026), veröffentlicht.

1. Beyond visual realism: assessing coronary artery dominance diversity in AI-generated synthetic coronary computed tomography angiography images

   Ghanaat, A., Seyfarth, M., Ayx, I., Schoenberg, S. O., Engelhardt, S., Dar, S.

   DOI ↗

2. Latent diffusion for single-pass full 4D cine cardiac magnetic resonance imaging synthesis with spatiotemporal autoencoding

   Seyfarth, M., Mueller, S. K., Dar, S., Engelhardt, S.

   DOI ↗

3. Predicting worsening and mortality in heart failure: a novel deep learning approach using echocardiographic data outperforms established biomarkers

   Romano-Martinez, A., Kontohow-Beckers, K., Zeid, S., Krolevets, M., Mueller, S. K., Lurz, P., … Wild, P. S.

   DOI ↗

4. Myocardial motion curves from CMR: an automated approach to visualize complex deformation patterns and comparison of healthy and diseased cohorts

   Kiekenap, J., Mueller, S. K., Köhler, S., Frey, N., Engelhardt, S.

   DOI ↗

5. Deep neural network-driven infrared thermography for diagnostics and therapy monitoring of peripheral arterial disease

   Hillen, B., Schäffer, L. C., Andrés López, D., Weber, V., Zentgraf, S., Schömer, E., … Simon, P.

   DOI ↗

ESC Congress 202529. Aug. – 1. Sep. 2025

1. Deep learning-based prediction of cardiac blood biomarkers from echocardiograms improves prognosis

   PosterRomano-Martinez, A., Kontohow-Beckers, K., Zeid, S., Mueller, S. K., Prochaska, J. H., Lurz, P., … Wild, P. S.

Heart Failure 2025 (48th Heart Failure Congress)17.–20. Mai 2025

1. Deep learning by vision transformer-based assessment of image quality in echocardiography improves prediction of heart failure-specific outcome

   PosterRomano-Martinez, A., Kontohow-Beckers, K., Zeid, S., Mueller, S. K., Prochaska, J. H., Lurz, P., … Wild, P. S.

ESSB Conference 2025

1. spCellEval (spatial proteomics cell phenotyping evaluation): benchmarking cell-phenotyping methods for antibody-based multiplexed imaging

   PosterHada, A., Hatscher, L., Chazotte, M., Tanevski, J., Schapiro, D.