Evidence map›Paper›PMID 37958050›Full record

ReviewHealthcare (Basel, Switzerland)2023

The Role of ChatGPT in the Advancement of Diagnosis, Management, and Prognosis of Cardiovascular and Cerebrovascular Disease.

David-Dimitris Chlorogiannis, Anastasios Apostolos, Anargyros Chlorogiannis, Leonidas Palaiodimos, George Giannakoulas, Sumant Pargaonkar, Sofia Xesfingi, Damianos G Kokkinidis

Open access · goldAbstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
1.0field-weighted citation impact, top 18% of its field
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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 25 citations in OpenAlex.

  1. Article
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  11. Depression and Coronary Artery Disease-Where We Stand?Journal of clinical medicine · 2025
    Review
  12. Article
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  18. Review
  19. Based on Medicine, The Now and Future of Large Language Models.Cellular and molecular bioengineering · 2024
    Review
  20. Article
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

8 authors at 7 institutions in 3 countries.

David-Dimitris ChlorogiannisDepartment of Radiology, Brigham and Women's Hospital, Boston, MA 02115, USA.
Anastasios ApostolosFirst Department of Cardiology, School of Medicine, National Kapodistrian University of Athens, Hippokrateion General Hospital of Athens, 115 27 Athens, Greece.ORCID 0000-0003-2616-7952
Anargyros ChlorogiannisDepartment of Health Economics, Policy and Management, Karolinska Institutet, 171 77 Stockholm, Sweden.
Leonidas PalaiodimosDivision of Hospital Medicine, Jacobi Medical Center, NYC H+H, Albert Einstein College of Medicine, New York, NY 10461, USA.ORCID 0000-0003-4682-5991
George GiannakoulasDepartment of Cardiology, AHEPA University Hospital, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece.ORCID 0000-0001-7491-6319
Sumant PargaonkarDivision of Hospital Medicine, Jacobi Medical Center, NYC H+H, Albert Einstein College of Medicine, New York, NY 10461, USA.ORCID 0000-0002-2568-2664
Sofia XesfingiDepartment of Economics, University of Piraeus, 185 34 Piraeus, Greece.
Damianos G KokkinidisSection of Cardiovascular Medicine, Yale University School of Medicine, New Haven, CT 06510, USA.
Jacobi Medical Center · USAristotle University of Thessaloniki · GRBrigham and Women's Hospital · USKarolinska Institutet · SENational and Kapodistrian University of Athens · GRUniversity of Piraeus · GRYale University · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Cardiovascular and cerebrovascular disease incidence has risen mainly due to poor control of preventable risk factors and still constitutes a significant financial and health burden worldwide. ChatGPT is an artificial intelligence language-based model developed by OpenAI. Due to the model's unique cognitive capabilities beyond data processing and the production of high-quality text, there has been a surge of research interest concerning its role in the scientific community and contemporary clinical practice. To fully exploit ChatGPT's potential benefits and reduce its possible misuse, extreme caution must be taken to ensure its implications ethically and equitably. In this narrative review, we explore the language model's possible applications and limitations while emphasizing its potential value for diagnosing, managing, and prognosis of cardiovascular and cerebrovascular disease.

Indexed as

cardiovascular diseasecerebrovascular diseasechatGPTdiagnosislanguage-based modelsmyocardial infarctionstroketreatment

Identifiers

PMID37958050
PMCPMC10648908
OpenAlexW4388424473

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.