Health Trials

MAchine Learning to Boost the Early Diagnosis of Acute Cardiovascular Conditions

ConditionsAcute Cardiovascular DiseaseST-segment Elevation Myocardial Infarction (STEMI)NSTEMI - Non-ST Segment Elevation MI
Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
Age18+
SponsorUniversity Hospital, Basel, Switzerland

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.

Eligibility criteria

Qualifiers

None

Disqualifiers

age < 18 years old

patients presenting in cardiogenic shock

chronic terminal kidney failure requiring dialysis

Trial design

Treatments tested in this trial

  • Machine learning based development of a diagnostic tool for acute cardiovascular disease

Treatment groups

200,000 Participants
are divided into 1 treatment group

Sponsors and collaborators

University Hospital, Basel, Switzerland

Lead sponsor

University of Basel

Collaborator

Source ClinicalTrials.gov