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Prognostic significance of explainable machine learning-defined type 2 myocardial infarction: unmasking a high-risk phenotype in multicenter data

29 August 2026 (09:15 - 10:00)
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Congress Presentation Part of: Myocardial infarction: artificial intelligence prediction and prognosis Machine Learning ESC2026 Premium Access ESC Congress 2026 European Society of Cardiology

About the speaker

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Professor Kang-Yin Chen

2nd Hospital of Tianjin Medical University, Tianjin (China)

6 More presentations in this session

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AI-ECG prediction of long-term adverse cardiovascular outcomes in post myocardial infarction patients
Mr L. Lovatelli (GB)
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Chest pain virtual ward (CPVW): a prospective analysis of a novel care model for low-risk acute coronary syndrome
Doctor T. Chakraborty (London, GB)
Abstract Slides Video
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The joint impact of frailty and premature myocardial infarction on one-year outcomes：biological vulnerability versus chronological age
Doctor R. Guo (Tianjin, CN)
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Machine learning-based survival models integrating quantitative flow ratio to predict in-stent restenosis after percutaneous coronary intervention
Professor T. Liu (Tianjin, CN)
Abstract Slides
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Impact of intra-patient variability of artificial intelligence and machine learning models on the diagnosis of myocardial infarction
Mr W. Zeng (Basel, CH)
Abstract Slides Video

Access the full session

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Myocardial infarction: artificial intelligence prediction and prognosis

The Event

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ESC Congress 2026

29 August 2026 09:15 CET
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