Machine learning based insights into cardiomyopathy and heart failure research: a bibliometric analysis from 2005 to 2024

Machine learning based insights into cardiomyopathy and heart failure research: a bibliometric analysis from 2005 to 2024

BackgroundCardiomyopathy and heart failure are among the most critical challenges in modern cardiology, with increasing attention to the integration of machine learning (ML) and artificial intelligence (AI) for diagnostics, risk prediction, and therapeutic strategies. This study was aimed at evaluat...

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Bibliographic Details
Main Authors: Muhammad Junaid Akram, Asad Nawaz, Yuan Yuxing, Jinpeng Zhang, Huang Haixin, Lingjuan Liu, Xu Qian, Jie Tian
Format: Article
Language:English
Published: Frontiers Media S.A. 2025-07-01
Series:Frontiers in Medicine
Subjects:
cardiomyopathy
heart failure
bibliometric
VOSviewer
CiteSpace
machine learning
Online Access:https://www.frontiersin.org/articles/10.3389/fmed.2025.1602077/full
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https://www.frontiersin.org/articles/10.3389/fmed.2025.1602077/full

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