Evidence map›Paper›PMID 36889874›Full record

ArticleJournal of the American College of Cardiology2023

Can Machine Learning Disrupt the Prediction of Sudden Death?

Sanjiv M Narayan, Albert J Rogers

Abstract readEditorialComment
In one paragraph

Article in Journal of the American College of Cardiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. The digital journey: 25 years of digital development in electrophysiology from an Europace perspective.Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology · 2023
    Review
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Sanjiv M NarayanDepartment of Medicine, Cardiovascular Institute, Computational Arrhythmia Research Laboratory, Stanford University School of Medicine, Stanford, California, USA. Electronic address: sanjiv1@stanford.edu.
Albert J RogersDepartment of Medicine, Cardiovascular Institute, Computational Arrhythmia Research Laboratory, Stanford University School of Medicine, Stanford, California, USA. Electronic address: https://twitter.com/ajrogers_md.

Funding

The Dynamics of Human Atrial FibrillationR01HL083359 · NHLBI · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI Sanjiv M Narayan · 2008 to 2026
$7.9M
Machine Learning in Atrial FibrillationR01HL149134 · NHLBI · STANFORD UNIVERSITY · PI NARAYAN, SANJIV M · 2020 to 2024
$3.8M
Machine Learning for Ventricular ArrhythmiasR01HL162260 · NHLBI · STANFORD UNIVERSITY · PI Sanjiv M Narayan · 2023 to 2026
$2.5M
Computational Medicine in the Heart, Integrated Training ProgramT32HL166155 · NHLBI · STANFORD UNIVERSITY · PI Alison L Marsden, Sanjiv M Narayan · 2023 to 2026
$2.0M
Electrical Mapping Signatures of Adverse Structural and Functional Remodeling in Ventricular ArrhythmiaK23HL166977 · NHLBI · STANFORD UNIVERSITY · PI Albert Joseph Rogers · 2023 to 2026
$680k
NHLBI NIH HHS K23 HL166977NHLBI NIH HHS L30 HL143631NHLBI NIH HHS R01 HL083359NHLBI NIH HHS R01 HL149134NHLBI NIH HHS R01 HL162260NHLBI NIH HHS T32 HL166155
6 · The paper itself

Abstract

PubMed holds no abstract for this paper.

Indexed as

Defibrillators, ImplantableTachycardia, VentricularDeath, SuddenDeath, Sudden, CardiacHumansMachine LearningVentricular Fibrillationartificial intelligenceimplantable defibrillator shocksmachine learningventricular fibrillationventricular tachycardia

Identifiers

PMID36889874
PMCPMC10984642

What OpenQuestion holds

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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.