TY - JOUR
T1 - Application of artificial intelligence in the diagnosis and treatment of cardiac arrhythmia
AU - Guo, Rong Xin
AU - Tian, Xu
AU - Bazoukis, George
AU - Tse, Gary
AU - Hong, Shenda
AU - Chen, Kang Yin
AU - Liu, Tong
N1 - Publisher Copyright:
© 2024 Wiley Periodicals LLC.
PY - 2024/6
Y1 - 2024/6
N2 - 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.
AB - 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.
KW - artificial intelligence
KW - cardiac arrhythmia
KW - chat-GPT
UR - http://www.scopus.com/inward/record.url?scp=85192258648&partnerID=8YFLogxK
U2 - 10.1111/pace.14995
DO - 10.1111/pace.14995
M3 - Review article
C2 - 38712484
AN - SCOPUS:85192258648
SN - 0147-8389
VL - 47
SP - 789
EP - 801
JO - PACE - Pacing and Clinical Electrophysiology
JF - PACE - Pacing and Clinical Electrophysiology
IS - 6
ER -