Artificial Intelligence System for Early Warning of Adverse Events in Acute Myocardial Infarction
NCT ID: NCT07139860
Last Updated: 2025-08-24
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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RECRUITING
1400 participants
OBSERVATIONAL
2022-11-26
2026-12-31
Brief Summary
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Does an AI-based early warning system improve the assessment and prediction of adverse events across the full course of AMI care (from prevention to diagnosis, treatment, and rehabilitation)?
Participants who are receiving routine medical care for AMI in tertiary hospitals will have their multimodal medical data (clinical records, diagnostic tests, imaging, treatment pathways) collected and analyzed. Data will be integrated using innovative cross-modal representation methods and predictive models. The study will follow patients during their hospital stay and subsequent clinical follow-up to evaluate the feasibility, accuracy, and clinical value of the AI-based early warning system.
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Detailed Description
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Conditions
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Study Design
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COHORT
OTHER
Study Groups
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BFH
group1
No interventions assigned to this group
AZH
group2
No interventions assigned to this group
Eligibility Criteria
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Inclusion Criteria
Exclusion Criteria
18 Years
ALL
No
Sponsors
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Hui Chen
OTHER
Responsible Party
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Hui Chen
PHD
Locations
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Beijing Friendship Hospital
Beijing, , China
Countries
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Central Contacts
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Facility Contacts
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Other Identifiers
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BFH2023063001
Identifier Type: -
Identifier Source: org_study_id
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