Evidence map›Paper›PMID 38247435›Full record

ReviewCardiology journal2024

Advancements in artificial intelligence-driven techniques for interventional cardiology.

Zofia Rudnicka, Agnieszka Pręgowska, Kinga Glądys, Mark Perkins, Klaudia Proniewska

Open access · goldAbstract readReview
In one paragraph

Review in Cardiology journal, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
6.9field-weighted citation impact, top 3% 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

3 citing papers in PubMed, 17 citations in OpenAlex.

  1. Review
  2. Review
  3. Review
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

5 authors at 4 institutions in 2 countries.

Zofia RudnickaInstitute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.
Agnieszka PręgowskaInstitute of Fundamental Technological Research, Polish Academy of Sciences, Warsaw, Poland.
Kinga GlądysJagiellonian University Medical College, Krakow, Poland.
Mark PerkinsCollegium Prometricum, the Business School for Healthcare, Sopot, Poland.
Klaudia ProniewskaDepartment of Bioinformatics and Telemedicine, Jagiellonian University Medical College, Krakow, Poland. klaudia.proniewska@uj.edu.pl.ORCID 0000-0002-8160-007X
Jagiellonian University · PLInstitute of Fundamental Technological Research · PLPolish Academy of Sciences · PLRoyal Society of Arts · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This paper aims to thoroughly discuss the impact of artificial intelligence (AI) on clinical practice in interventional cardiology (IC) with special recognition of its most recent advancements. Thus, recent years have been exceptionally abundant in advancements in computational tools, including the development of AI. The application of AI development is currently in its early stages, nevertheless new technologies have proven to be a promising concept, particularly considering IC showing great impact on patient safety, risk stratification and outcomes during the whole therapeutic process. The primary goal is to achieve the integration of multiple cardiac imaging modalities, establish online decision support systems and platforms based on augmented and/or virtual realities, and finally to create automatic medical systems, providing electronic health data on patients. In a simplified way, two main areas of AI utilization in IC may be distinguished, namely, virtual and physical. Consequently, numerous studies have provided data regarding AI utilization in terms of automated interpretation and analysis from various cardiac modalities, including electrocardiogram, echocardiography, angiography, cardiac magnetic resonance imaging, and computed tomography as well as data collected during robotic-assisted percutaneous coronary intervention procedures. Thus, this paper aims to thoroughly discuss the impact of AI on clinical practice in IC with special recognition of its most recent advancements.

Indexed as

Artificial IntelligenceCardiologyCardiovascular DiseasesHumansPercutaneous Coronary Interventionartificial intelligence (AI)augmented and/or virtual realitiesautomatic medical systemscardiac modalitiesinterventional cardiology (IC)

Identifiers

PMID38247435
PMCPMC11076027
OpenAlexW4391106879

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.