Evidence map›Paper›PMID 37480904›Full record

ReviewJACC. Cardiovascular imaging2023

Proceedings of the NHLBI Workshop on Artificial Intelligence in Cardiovascular Imaging: Translation to Patient Care.

Damini Dey, Rima Arnaout, Sameer Antani, Aldo Badano, Louis Jacques, Huiqing Li, Tim Leiner, Edward Margerrison, Ravi Samala, Partho P Sengupta and 5 more

Abstract readReview
PubMed Full text at PMC Publisher
In one paragraph

Review in JACC. Cardiovascular imaging, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 1 pooled it
–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

18 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Guideline
  2. Review
  3. Article
  4. Review
  5. Article
  6. [Role of echocardiography in the assessment of right ventricular function in pulmonary hypertension].Zhong nan da xue xue bao. Yi xue ban = Journal of Central South University. Medical sciences · 2026
    Review
  7. Article
  8. Article
  9. Article
  10. Review
  11. Review
  12. Article
  13. Review
  14. Review
  15. bioRxiv : the preprint server for biology · 2024
    Article
  16. Review
  17. Article
  18. ChatGPT Helped Me Write This Talk Title, but Can It Read an Echocardiogram?Journal of the American Society of Echocardiography : official publication of the American Society of Echocardiography · 2023
    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

15 authors.

Damini DeyCedars-Sinai Medical Center, Los Angeles, California, USA.
Rima ArnaoutDepartment of Medicine, University of California-San Francisco, San Francisco, California, USA. Electronic address: rima.arnaout@ucsf.edu.
Sameer AntaniNational Library of Medicine, National Institutes of Health, Bethesda, Maryland, USA.
Aldo BadanoOffice of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
Louis JacquesADVI Health, LLC, Washington, DC, USA.
Huiqing LiNational Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Tim LeinerMayo Clinic, Rochester, Minnesota, USA.
Edward MargerrisonOffice of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
Ravi SamalaOffice of Science and Engineering Laboratories, Center for Devices and Radiological Health, Food and Drug Administration, Silver Spring, Maryland, USA.
Partho P SenguptaDepartment of Medicine, Rutgers University, Newark, New Jersey, USA.
Sanjiv J ShahDepartment of Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois, USA.
Piotr SlomkaCedars-Sinai Medical Center, Los Angeles, California, USA.
Michelle C WilliamsCentre for Cardiovascular Science, University of Edinburgh, Edinburgh, United Kingdom; British Heart Foundation Data Science Centre, London, United Kingdom.
W Patricia BandettiniNational Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.
Vandana SachdevNational Heart, Lung, and Blood Institute, National Institutes of Health, Bethesda, Maryland, USA.

Funding

HeartShare DeCODE-HF: Data translation center to Combine Omics, Deep phenotyping, and Electronic health records for Heart Failure subtypes and treatment targetsU54HL160273 · NHLBI · NORTHWESTERN UNIVERSITY AT CHICAGO · PI Abel N. Kho, Yuan Luo · 2021 to 2026
$19.0M
Machine learning and artificial intelligence research for clinical medical image processingZIALM010018 · NLM · NATIONAL LIBRARY OF MEDICINE · PI ANTANI, SAMEER · 2021 to 2025
$9.0M
Toward efficient performance for deep learning on medical imagingR01HL150394 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI Rima Arnaout · 2020 to 2026
$6.2M
Patient-specific Outcome Prediction from Cardiovascular Multimodality Imaging by Artificial IntelligenceR35HL161195 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI Piotr J Slomka · 2022 to 2026
$5.0M
Integrated prediction of cardiovascular events by automated coronary plaque and pericoronary adipose tissue quantification from CT AngiographyR01HL148787 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI DEY, DAMINI · 2020 to 2023
$3.0M
Machine learning for the automated identification and tracking of rare myocardial diseasesR01HL140731 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · PI MACRAE, CALUM A., SHAH, SANJIV J · 2018 to 2021
$2.8M
Precision Medicine for Dilated Cardiomyopathy—Novel Assessment of Cardiac Mechanics via Speckle Tracking Echocardiography to Identify Early PhenotypesR01HL149423 · NHLBI · OHIO STATE UNIVERSITY · PI HERSHBERGER, RAY E., KINNAMON, DANIEL DAVIS · 2019 to 2022
$1.6M
Effect of Intensive Medical Treatment on Quantified Coronary Artery Plaque Components with Serial Coronary CTA in Women with Non-Obstructive CADR01HL151266 · NHLBI · CEDARS-SINAI MEDICAL CENTER · PI DEY, DAMINI, TAMARAPPOO, BALAJI K. · 2020 to 2023
$1.6M
British Heart Foundation FS/ICRF/20/26002NHLBI NIH HHS R01 HL140731NHLBI NIH HHS R01 HL148787NHLBI NIH HHS R01 HL149423NHLBI NIH HHS R01 HL150394NHLBI NIH HHS R01 HL151266NHLBI NIH HHS R35 HL161195NHLBI NIH HHS U54 HL160273
6 · The paper itself

Abstract

Artificial intelligence (AI) promises to revolutionize many fields, but its clinical implementation in cardiovascular imaging is still rare despite increasing research. We sought to facilitate discussion across several fields and across the lifecycle of research, development, validation, and implementation to identify challenges and opportunities to further translation of AI in cardiovascular imaging. Furthermore, it seemed apparent that a multidisciplinary effort across institutions would be essential to overcome these challenges. This paper summarizes the proceedings of the National Heart, Lung, and Blood Institute-led workshop, creating consensus around needs and opportunities for institutions at several levels to support and advance research in this field and support future translation.

Indexed as

Artificial IntelligenceCardiovascular SystemHumansNational Heart, Lung, and Blood Institute (U.S.)Patient CarePredictive Value of TestsUnited StatesAI algorithmsartificial intelligencecardiovascular imagingdata sciencedeep learningmachine learning

Identifiers

PMID37480904
PMCPMC10524663

What OpenQuestion holds

Textmetadata
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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.