Evidence map›Paper›PMID 36204566›Full record

ReviewFrontiers in cardiovascular medicine2022

Artificial intelligence in cardiac magnetic resonance fingerprinting.

Carlos Velasco, Thomas J Fletcher, René M Botnar, Claudia Prieto

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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.

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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Recent Progress of Cardiac MRI for Nuclear Medicine Professionals.Nuclear medicine and molecular imaging · 2024
    Review
  4. Article
  5. Article
  6. Review
  7. Review
  8. The future of cardiovascular magnetic resonance: All-in-one vs. real-time (Part 1).Journal of cardiovascular magnetic resonance : official journal of the Society for Cardiovascular Magnetic Resonance · 2024
    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

4 authors.

Carlos VelascoSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Thomas J FletcherSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
René M BotnarSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.
Claudia PrietoSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, United Kingdom.

Funding

British Heart Foundation PG/18/59/33955British Heart Foundation RG/20/1/34802
6 · The paper itself

Abstract

Magnetic resonance fingerprinting (MRF) is a fast MRI-based technique that allows for multiparametric quantitative characterization of the tissues of interest in a single acquisition. In particular, it has gained attention in the field of cardiac imaging due to its ability to provide simultaneous and co-registered myocardial T

Indexed as

artificial intelligence (AI)cardiac magnetic resonance (CMR)cardiac MRFmagnetic resonance fingerprinting (MRF)multiparametric imaging

Identifiers

PMID36204566
PMCPMC9530662

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.