Evidence map›Paper›PMID 37012018›Full record

ArticleBMJ open2023

Artificial intelligence-based mining of electronic health record data to accelerate the digital transformation of the national cardiovascular ecosystem: design protocol of the CardioMining study.

Athanasios Samaras, Alexandra Bekiaridou, Andreas S Papazoglou, Dimitrios V Moysidis, Grigorios Tsoumakas, Panagiotis Bamidis, Grigorios Tsigkas, George Lazaros, George Kassimis, Nikolaos Fragakis and 7 more

Registry-linked trialAbstract read
In one paragraph

Article in BMJ open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05176769 (The Usefulness of Artificial Intelligence for Automated Extraction and Processing of Clinical Data From Electronic Medical Records), which is not on this map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

NCT05176769 recruitingnot on this map

The Usefulness of Artificial Intelligence for Automated Extraction and Processing of Clinical Data From Electronic Medical Records (CardioMining-AI)

TypeobservationalSponsorAHEPA University HospitalRan2022 to 2026Enrolled60,000ConditionsArtificial Intelligence, Machine Learning, Electronic Medical Records
3 · Its place in the literature

Who cites it

13 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

17 authors.

Athanasios Samaras1st Department of Cardiology, University General Hospital of Thessaloniki AHEPA, Thessaloniki, Greece.
Alexandra Bekiaridou1st Department of Cardiology, University General Hospital of Thessaloniki AHEPA, Thessaloniki, Greece.
Andreas S Papazoglou1st Department of Cardiology, University General Hospital of Thessaloniki AHEPA, Thessaloniki, Greece.
Dimitrios V Moysidis1st Department of Cardiology, University General Hospital of Thessaloniki AHEPA, Thessaloniki, Greece.
Grigorios TsoumakasSchool of Informatics, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Panagiotis BamidisMedical Physics and Digital Innovation Laboratory, School of Medicine, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Grigorios TsigkasDepartment of Cardiology, University Hospital of Patras, Rio Patras, Greece.
George Lazaros1st Cardiology Department, "Hippokration" General Hospital, University of Athens Medical School, Athens, Greece.
George Kassimis1st Department of Cardiology, University General Hospital of Thessaloniki AHEPA, Thessaloniki, Greece.ORCID 0000-0003-4485-5054
Nikolaos Fragakis2nd Cardiology Department, Hippokrateion General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Vassilios Vassilikos3rd Cardiology Department, Hippokrateion General Hospital, Aristotle University of Thessaloniki, Thessaloniki, Greece.
Ioannis ZarifisDepartment of Cardiology, "George Papanikolaou" General Hospital, Thessaloniki, Greece.
Dimitrios N TziakasDepartment of Cardiology, Democritus University of Thrace, University Hospital of Alexandroupolis, Alexandroupolis, Greece.
Konstantinos Tsioufis1st Cardiology Department, "Hippokration" General Hospital, University of Athens Medical School, Athens, Greece.
Periklis DavlourosDepartment of Cardiology, University Hospital of Patras, Rio Patras, Greece.
George Giannakoulas1st Department of Cardiology, University General Hospital of Thessaloniki AHEPA, Thessaloniki, Greece ggiannakoulas@auth.gr.ORCID 0000-0001-7491-6319
CardioMining Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionMining of electronic health record (EHRs) data is increasingly being implemented all over the world but mainly focuses on structured data. The capabilities of artificial intelligence (AI) could reverse the underusage of unstructured EHR data and enhance the quality of medical research and clinical care. This study aims to develop an AI-based model to transform unstructured EHR data into an organised, interpretable dataset and form a national dataset of cardiac patients. METHODS AND ANALYSIS: CardioMining is a retrospective, multicentre study based on large, longitudinal data obtained from unstructured EHRs of the largest tertiary hospitals in Greece. Demographics, hospital administrative data, medical history, medications, laboratory examinations, imaging reports, therapeutic interventions, in-hospital management and postdischarge instructions will be collected, coupled with structured prognostic data from the National Institute of Health. The target number of included patients is 100 000. Natural language processing techniques will facilitate data mining from the unstructured EHRs. The accuracy of the automated model will be compared with the manual data extraction by study investigators. Machine learning tools will provide data analytics. CardioMining aims to cultivate the digital transformation of the national cardiovascular system and fill the gap in medical recording and big data analysis using validated AI techniques. ETHICS AND DISSEMINATION: This study will be conducted in keeping with the International Conference on Harmonisation Good Clinical Practice guidelines, the Declaration of Helsinki, the Data Protection Code of the European Data Protection Authority and the European General Data Protection Regulation. The Research Ethics Committee of the Aristotle University of Thessaloniki and Scientific and Ethics Council of the AHEPA University Hospital have approved this study. Study findings will be disseminated through peer-reviewed medical journals and international conferences. International collaborations with other cardiovascular registries will be attempted. TRIAL REGISTRATION NUMBER: NCT05176769.

Indexed as

Cardiovascular SystemElectronic Health RecordsAftercareArtificial IntelligenceEcosystemHumansMulticenter Studies as TopicPatient DischargeResearch DesignRetrospective StudiesCARDIOLOGYHealth informaticsHeart failureIschaemic heart diseaseRisk management

Identifiers

PMID37012018
PMCPMC10083759

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Registered trials

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.