MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions
Recruiting
Observational Study
Acute Cardiovascular Disease
ST-segment Elevation Myocardial Infarction (STEMI)
NSTEMI - Non-ST Segment Elevation MI
No Placebo Group
Every participant receives an active treatment — no one gets a placebo.
No Study Drug
Researchers observe your health over time — no experimental treatment is given.
At a Glance
- Age
- 18 and older
- Sex
- Any
- Study type
- Observational
- Participants needed
- 200,000 (estimated)
- Sponsor
- University Hospital, Basel, Switzerland · Other
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About This Trial
The research project aims to develop clinical decision support tools integrating established diagnostic variables and machine learning (ML) models for rapid diagnosis of acute life-threatening cardiovascular conditions in emergency department (ED) patients with chest pain or dyspnea with the ultimate goal of Improved diagnostic accuracy, faster patient management, and reduced medical errors.
Trial Locations
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Eligibility Criteria
Inclusion Criteria:
• Acute cardiovascular disease (ACVD)
Exclusion Criteria
* age \< 18 years old
* patients presenting in cardiogenic shock
* chronic terminal kidney failure requiring dialysis
Contacts