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MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions

RECRUITINGSponsored by University Hospital, Basel, Switzerland
Actively Recruiting
SponsorUniversity Hospital, Basel, Switzerland
Started2024-04-01
Est. completion2027-03
Eligibility
Age18 Years+
Healthy vol.Accepted
View on ClinicalTrials.gov →

NCT06927791

Summary

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.

Eligibility

Age: 18 Years+Healthy volunteers accepted
Inclusion Criteria:

• Acute cardiovascular disease (ACVD)

Exclusion Criteria

* age \< 18 years old
* patients presenting in cardiogenic shock
* chronic terminal kidney failure requiring dialysis

Conditions4

Acute Cardiovascular DiseaseHeart DiseaseNSTEMI - Non-ST Segment Elevation MIST-segment Elevation Myocardial Infarction (STEMI)

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