Evidence map›Paper›PMID 40695457›Full record

ReviewThe Journal of physiology2026

Advances in cardiac devices and bioelectronics augmented with artificial intelligence.

Charles Stark, Eric Rytkin, Andrei Alexandru Mircea, Igor R Efimov

Abstract readReview
In one paragraph

Review in The Journal of physiology, 2026. 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. Review
  2. 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.

Charles StarkDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, USA.ORCID https://orcid.org/0000-0002-9117-7842
Eric RytkinDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, USA.ORCID https://orcid.org/0000-0003-2511-0655
Andrei Alexandru MirceaDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, USA.
Igor R EfimovDepartment of Biomedical Engineering, Northwestern University, Evanston, IL, USA.ORCID https://orcid.org/0000-0002-1483-5039

Funding

Medical Scientist Training ProgramT32GM144295 · NIGMS · NORTHWESTERN UNIVERSITY AT CHICAGO · PI ALAN R HAUSER · 2022 to 2026
$9.1M
High-Definition Conformal Electronics for VT/VFR01HL141470 · NHLBI · NORTHWESTERN UNIVERSITY · PI EFIMOV, IGOR R · 2019 to 2022
$2.5M
Fondation Leducq (Leducq Foundation) Bioelectronics for NeurocardiologyHHS | NIH | All of Us Research Program (AoURP) R01HL141470HHS | NIH | All of Us Research Program (AoURP) T32GM144295
6 · The paper itself

Abstract

Diagnostic bioelectronics such as the electrocardiogram have become increasingly prevalent in the management of cardiovascular diseases like atrial fibrillation. While these devices provide meaningful clinical value, their complex and profuse data output requires considerable labour and training from clinicians to diagnose disease. This abundant production of complex data has made diagnostic bioelectronics a prime target for artificial intelligence (AI) integration. AI-integrated diagnostic bioelectronics have already left the clinic as widely prevalent wearable smartwatches equipped with single-lead electrocardiography sensors. Meanwhile, substantial innovation is also taking place at the intersection of other sensing modalities in the form of edge computing. Here, we overview the implementation and embedding of AI into diagnostic bioelectronics of multiple sensing modalities, including electrocardiography, photoplethysmography, echocardiography, and others, and discuss the recent advances made by medical device companies and researchers alike at the interface between the heart and AI.

Indexed as

Artificial IntelligenceWearable Electronic DevicesAnimalsDigital HealthElectrocardiographyHumansArtificial intelligencebioelectronicscardiovascular diseasedeep learningmachine learningwearables

Identifiers

PMID40695457
PMCPMC13327763

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.