Using artificial intelligence to analyze clinical data from electronic medical records
Official title: The Usefulness of Artificial Intelligence for Automated Extraction and Processing of Clinical Data From Electronic Medical Records (CardioMining-AI)
Run by AHEPA University Hospital · NCT05176769 · Data updated 2026-11-12
This study is testing whether using artificial intelligence can help doctors quickly and accurately analyze patient notes from hospital records to improve heart care.
Quick facts
| Study type | Observational |
|---|---|
| Ages | 18 Years and up |
| Sex | All |
| Enrollment | 60000 (estimated) |
| Sponsor | AHEPA University Hospital Academic / other |
| Locations | 9 sites (Alexandroupoli and 8 other locations) |
| Status | Recruiting |
| Started | January 14, 2022 |
| Main results expected | December 1, 2030 |
| Study ends | March 1, 2032 |
| Registry record updated | October 27, 2026 |
| Trial ID | NCT05176769 on ClinicalTrials.gov |
Is this trial a fit for you?
✓Likely a good fit
Ideal candidates for this study are hospitalized patients in cardiology departments whose medical records are electronically stored.
✕Probably not a fit
Patients who died during hospitalization and do not have a discharge letter will not benefit from this study.
A plain-English reading of the study's rules. Only the study team can confirm whether you qualify.
What this trial studies
This study aims to demonstrate the effectiveness of artificial intelligence and machine learning in automating the extraction and processing of large volumes of unstructured clinical data from electronic medical records. By leveraging AI algorithms, the study seeks to enhance the speed, reliability, and accuracy of data analysis, which is crucial for improving risk stratification models in healthcare. The focus is on collecting clinical notes from hospitalized patients in cardiology departments across various hospitals in Greece, addressing the challenges posed by manual data processing. The ultimate goal is to improve diagnostic and therapeutic accuracy while ensuring patient privacy.
Why it matters
Potential benefit: If successful, this approach could significantly streamline data processing in healthcare, leading to better patient outcomes and more efficient healthcare systems.
How similar studies have gone: Other studies have shown promise in using AI for data analysis in healthcare, indicating that this approach could be effective.
Who can join: the full rules
Show full inclusion / exclusion criteria
Inclusion Criteria: * Hospitalised patients in Cardiology Departments in Greece * Patients whose medical records are electronically stored in each hospital's computer/information systems Exclusion Criteria: * Patients that died during hospitalization, and thus no discharge letter was issued
Where it's running
-
1st Department of Cardiology, Hippokration General Hospital
Athens, Greece Recruiting -
University General Hospital of Larissa, University of Thessaly
Larissa, Greece Recruiting -
Department of Cardiology, University of Patras Medical School
Pátrai, Greece Recruiting -
1st Cardiology Department, AHEPA University Hospital
Thessaloniki, Greece Recruiting -
Cardiology Department, George Papanikolaou General Hospital
Thessaloniki, Greece Recruiting -
Laboratory of Medical Physics, Aristotle University of Thessaloniki
Thessaloniki, Greece Recruiting
Show 3 more locations
-
University Cardiology Clinic, Democritus University of Thrace
Alexandroupoli, Greece Not yet recruiting -
Department of Cardiology, Heraklion University Hospital
Heraklion, Greece Not yet recruiting -
3rd Cardiology Department, Hippokration Hospital
Thessaloniki, Greece Not yet recruiting
Study contacts
- Study coordinator: George Giannakoulas, MD, PhD
- Email: ggiannakoulas@auth.gr
- Phone: 2310994830
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How to take part
- Review the eligibility criteria above with your treating physician.
- Check the official listing on ClinicalTrials.gov for the latest contact details and recruitment status.
- Contact the study coordinator or principal investigator to ask for pre-screening. Pre-screening is free and never obligates you to enroll.