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Development and validation of a machine learning-based explainable predictive model for long-term outcomes in patients with high bleeding risk undergoing percutaneous coronary intervention

29 August 2025 (07:00 - 18:00)
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Congress Presentation Part of: Chronic coronary syndromes: artificial intelligence and other techniques Pharmacotherapy ESC Professional Premium Access ESC Congress 2025 European Society of Cardiology

About the speaker

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Doctor Junyan Zhang

West China Hospital, Sichuan University, Chengdu (China)

6 More presentations in this session

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Machine learning to simplify complex coronary small vessel diagnostics
Doctor D. Tan (Glasgow, GB)
Abstract Slides Video
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Noninvasive diagnosis of ischemia non-obstructive coronary using machine learning-assisted magnetocardiography
Mr X. Xu (Shanghai, CN)
Abstract Slides Video
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Discharge assessment of elderly patients with coronary heart disease based on machine learning
Doctor S. Yan (Beijing, CN)
Abstract Slides Video
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Real-world insights from an AI-ECG decision support platform: AI vs. blinded HCP STEMI ECG interpretation
Doctor A. Demolder (Aalst, BE) Doctor T. Kisova (Rome, IT)
Abstract Slides Video
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Machine learning for severe coronary artery disease: classification performance for screening and individualized risk prediction
Doctor C. Al Hageh (Abu Dhabi, AE)
Abstract Slides Video

Access the full session

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Chronic coronary syndromes: artificial intelligence and other techniques

The Event

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ESC Congress 2025

29 August - 1 September 2025
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ESC 365 is supported by

novartis Explore sponsored resources