Actively Recruiting
MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions
Led by University Hospital, Basel, Switzerland · Updated on 2025-04-15
200000
Participants Needed
1
Research Sites
152 weeks
Total Duration
On this page
Sponsors
U
University Hospital, Basel, Switzerland
Lead Sponsor
U
University of Basel
Collaborating Sponsor
AI-Summary
What this Trial Is About
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.
CONDITIONS
Official Title
MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Acute cardiovascular disease (ACVD)
You will not qualify if you...
- Age less than 18 years old
- Patients presenting in cardiogenic shock
- Chronic terminal kidney failure requiring dialysis
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 1 location
1
University Hospital Basel
Basel, Switzerland, 4031
Actively Recruiting
Research Team
J
Jasper Boeddinghaus, PD Dr. med.
CONTACT
I
Ivo Strebel, PhD
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
1
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