AI Algorithms in Prediction of ACS Based on Leukocyte Properties
- Disease/Condition
- Acute Coronary Syndrome,Angina Pectoris,NSTEMI - Non-ST Segment Elevation MI,STEMI - ST Elevation Myocardial Infarction
- Study type
- Observational
- Primary sponsor
- RobotDreams GmbH
- Location
- Graz, Austria
- Phase
- N/A
- Start date
- Feb 01, 2024
- End date
- Dec 31, 2026
- Enrollment
- 2700 participants
Training of AI models,Testing of AI models
The goal of this observational study is to find out if artificial intelligence (AI) can
 accurately predict acute coronary syndrome (ACS) using data on white blood cells in adults.
 The main question it aims to answer is:
 
 - Can AI algorithms based on white blood cell data predict ACS with accuracy comparable to
 that of high-sensitivity cardiac troponin (hs-cTn)? Researchers will look at how the AI
 model's predictions stack up against the standard hs-cTn blood tests to see which is more
 accurate in diagnosing ACS.
 
 Participants in this study will have already had blood tests as part of their usual care.
 Their previously collected health information and blood test results will be used to help
 train and test the AI algorithms. Participants will not undergo any new procedures for the
 study itself.
- Registry
- ClinicalTrials.gov
- Trial ID
- NCT06384846
- Type
- Non-Device Trial
Access comprehensive clinical trial information for NCT06384846 through Pure Global AI's free database. This phase not specified trial is sponsored by RobotDreams GmbH and is currently Recruiting. The study focuses on Acute Coronary Syndrome,Angina Pectoris,NSTEMI - Non-ST Segment Elevation MI,STEMI - ST Elevation Myocardial Infarction. Target enrollment is 2700 participants.
This page provides complete trial specifications, intervention details, outcomes, and location information. Pure Global AI offers free access to ClinicalTrials.gov data, helping medical device and pharmaceutical companies navigate clinical research efficiently.