MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions

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.

NCT Number	NCT06927791
Lead Sponsor	University Hospital, Basel, Switzerland Collaborators: University of Basel
Conditions	Acute Cardiovascular Disease, ST-segment Elevation Myocardial Infarction (STEMI), NSTEMI - Non-ST Segment Elevation MI
Enrollment	200,000 participants
Start Date	2024-04-01
Primary Completion	2027-03 (estimated)
Study Completion	2027-03 (estimated)
Updated on ClinicalTrials.gov	2025-04-15