Clinical Research Directory
Browse clinical research sites, groups, and studies.
MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions
Sponsor: University Hospital, Basel, Switzerland
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.
Key Details
Gender
All
Age Range
18 Years - Any
Study Type
OBSERVATIONAL
Enrollment
200000
Start Date
2024-04-01
Completion Date
2027-03
Last Updated
2025-04-15
Healthy Volunteers
No
Conditions
Interventions
Machine learning based development of a diagnostic tool for acute cardiovascular disease
MALBEC will be delivered through five integrated work packages (WP) encompassing: (0) platform development and implementation, (1) data pooling, (2) model development, (3) performance comparison, (4) performance validation, and (5) platform plugin
Locations (1)
University Hospital Basel
Basel, Switzerland