Deep Learning Model for High-Accuracy Classification of Premature Ventricular Contractions With Precordial Transition Zones in Leads V3 or V4

Authors

Yukiomi Tsuji (ORCID: https://orcid.org/0000-0003-4836-3057)
Yasuya Inden (ORCID: https://orcid.org/0000-0001-5732-5672)
Masaya Tachi
Kiichi Miyamae
Hiroyuki Miyazawa (ORCID: https://orcid.org/0000-0001-9282-1903)
Satoshi Yanagisawa (ORCID: https://orcid.org/0000-0002-0658-5498)
Masafumi Shimojo
Shun Kondo
Toyoaki Murohara
Tomoya Iwawaki (ORCID: https://orcid.org/0009-0000-2297-4146)
Takayuki Goto

Institutions

Nagoya University (JP)

Publication Details

Journal: Circulation Journal
Published: 2025-11-26
DOI: https://doi.org/10.1253/circj.cj-25-0534
Citations: 1
Primary Topic: Cardiac Arrhythmias and Treatments
Type: article
Field-Weighted Citation Impact: 1.39

Funders

Japan Lifeline

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article

Deep Learning Model for High-Accuracy Classification of Premature Ventricular Contractions With Precordial Transition Zones in Leads V3 or V4

Yukiomi Tsuji, Yasuya Inden, Masaya Tachi, Kiichi Miyamae et al.

Nov 26, 2025

1 citations

Circulation Journal

Cardiac Arrhythmias and Treatments

1.39

article

Deep Learning Model for High-Accuracy Classification of Premature Ventricular Contractions With Precordial Transition Zones in Leads V3 or V4

Yukiomi Tsuji, Yasuya Inden, Masaya Tachi, Kiichi Miyamae, Hiroyuki Miyazawa, Satoshi Yanagisawa, Masafumi Shimojo, Shun Kondo, Toyoaki Murohara, Tomoya Iwawaki, Takayuki Goto

November 26, 2025article en

1 citations

Abstract

No abstract available for this paper.

Circulation Journal

Nagoya University (JP)

Japan Lifeline

Openalex Percentile: Top 13%

Cardiac Arrhythmias and Treatments

1.39

DOI Open Access PDF OpenAlex

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