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(P2114) |
WATCH-BPM (comparing a wearable WATCH-type Blood Pressure Monitor with a conventional ambulatory blood pressure monitor and auscultatory sphygmomanometry) |
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A. Samol, M. Vaseekaran, S. Kaese, D. Görlich, M. Wiemer (Gronau (Westf.), Minden, Münster) |
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(P2115) |
Quantification of the Learning Progress in Minimally Invasive Mitral Valve Repair on a Patient-Specific Simulator |
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C. Wang, R. Karl, M. Karck, R. De Simone, G. Romano, S. Engelhardt, für die Studiengruppe: AICM (Heidelberg) |
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(P2116) |
Die PROGRESS Studie integriert Patientendaten mit Koronarmorphologie mit der Hilfe von Künstlicher Intelligenz (KI) |
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H. Nording, A. Constantz, H. Langer, J. Erdmann, PROGRESS , für die Studiengruppen: DZHK (Lübeck, Mannheim) |
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(P2117) |
Social media diffusion of a novel digital health approach: A social network analysis of the #TeleCheckAF project |
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K. Betz, J. J. van Haren, M. Gawalko, A.N.L. Hermans, R. M. Van der Velden, N. A. Pluymaekers, J. Hendriks, M. Manninger-Wünscher, J. Lemmink, D. Linz (Maastricht, LM Maastricht, NL; Adelaide, AU; Graz, AT) |
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(P2118) |
The Unmet Potential of Digital Workflow Analysis for Interventional Cardiology and Cardiac Surgery |
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J. Chen, G. Romano, B. Mayer, H. Kelm, J. Marx, G. Kostiuchik, L. Sharan, B. Preim, R. De Simone, M. Karck, S. Engelhardt (Heidelberg, Magdeburg) |
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(P2119) |
Development of a patient-centered app for cardiovascular patients using a questionnaire study in Germany |
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V. Oettinger, K. Kaier, T. Paulus, D. Westermann, M. Zehender (Freiburg im Breisgau, Bühl) |
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(P2120) |
Using Artificial Intelligence (AI) to optimize ECG based prediction of CAD and mortality – a comparison of different methods |
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J. Kampf, L. Vogel, I. Dykun, M. Totzeck, T. Rassaf, A.-A. Mahabadi (Essen) |
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(P2121) |
Artificial intelligence enhanced ECG can predict obstructive cardiovascular disease and death using secondary data |
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L. Vogel, J. Kampf, I. Dykun, M. Totzeck, T. Rassaf, A.-A. Mahabadi (Essen) |