Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia

Rong Xin Guo, Xu Tian, George Bazoukis, Gary Tse, Shenda Hong, Kang Yin Chen, Tong Liu

Research output: Contribution to journalReview articlepeer-review

2 Citations (Scopus)

Abstract

The rapid growth in computational power, sensor technology, and wearable devices has provided a solid foundation for all aspects of cardiac arrhythmia care. Artificial intelligence (AI) has been instrumental in bringing about significant changes in the prevention, risk assessment, diagnosis, and treatment of arrhythmia. This review examines the current state of AI in the diagnosis and treatment of atrial fibrillation, supraventricular arrhythmia, ventricular arrhythmia, hereditary channelopathies, and cardiac pacing. Furthermore, ChatGPT, which has gained attention recently, is addressed in this paper along with its potential applications in the field of arrhythmia. Additionally, the accuracy of arrhythmia diagnosis can be improved by identifying electrode misplacement or erroneous swapping of electrode position using AI. Remote monitoring has expanded greatly due to the emergence of contactless monitoring technology as wearable devices continue to develop and flourish. Parallel advances in AI computing power, ChatGPT, availability of large data sets, and more have greatly expanded applications in arrhythmia diagnosis, risk assessment, and treatment. More precise algorithms based on big data, personalized risk assessment, telemedicine and mobile health, smart hardware and wearables, and the exploration of rare or complex types of arrhythmia are the future direction.

Original languageEnglish
Pages (from-to)789-801
Number of pages13
JournalPACE - Pacing and Clinical Electrophysiology
Volume47
Issue number6
DOIs
Publication statusPublished - Jun 2024

Keywords

  • artificial intelligence
  • cardiac arrhythmia
  • chat-GPT

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