Using machine learning to improve early diagnosis of acute cardiovascular conditions

Is this trial a fit for you?

A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.

What this trial studies

This project aims to develop a clinical decision support tool that integrates established diagnostic variables with machine learning models to enhance the rapid diagnosis of acute cardiovascular diseases in emergency department patients presenting with chest pain or dyspnea. By utilizing advanced techniques such as deep transfer learning and automated machine learning, the study seeks to improve diagnostic accuracy, expedite patient management, and minimize medical errors. The research builds on previous large-scale studies in cardiovascular biomarker research and precision medicine, addressing the challenges of diagnosing life-threatening conditions in a timely manner.

Why it matters

Who can join: the full rules

Inclusion Criteria:

• Acute cardiovascular disease (ACVD)

Exclusion Criteria

* age \< 18 years old
* patients presenting in cardiogenic shock
* chronic terminal kidney failure requiring dialysis

Where it's running

• University Hospital Basel
  Basel, Switzerland Recruiting

Study contacts

• Principal investigator: Jasper Boeddinghaus, PD Dr. med. — University Hospital, Basel, Switzerland
• Study coordinator: Jasper Boeddinghaus, PD Dr. med.
• Email: jasper.boeddinghaus@usb.ch
• Phone: +41 61 32 87897

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How to take part

1. Review the eligibility criteria above with your treating physician.
2. Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
3. Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.