Tianjin Key Laboratory of lonic-Molecular Function of Cardiovascular Disease, Department of Cardiology, Tianjin Institute of Cardiology, Second Hospital of Tianjin Medical University, Tianjin, China.
Department of Cardiology, Larnaca General Hospital, Inomenon Polition Amerikis, Larnaca, Cyprus.
Pacing Clin Electrophysiol. 2024 Jun;47(6):789-801. doi: 10.1111/pace.14995. Epub 2024 May 7.
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.
计算能力、传感器技术和可穿戴设备的快速发展为心律失常治疗的各个方面提供了坚实的基础。人工智能(AI)在心律失常的预防、风险评估、诊断和治疗方面带来了重大变革。本文综述了 AI 在心房颤动、室上性心律失常、室性心律失常、遗传性通道病和心脏起搏诊断和治疗中的应用现状。此外,本文还探讨了最近备受关注的 ChatGPT 及其在心律失常领域的潜在应用。此外,通过使用 AI 识别电极错位或电极位置错误交换,可提高心律失常诊断的准确性。随着可穿戴设备的不断发展和普及,非接触式监测技术的出现极大地扩展了远程监测的范围。人工智能计算能力、ChatGPT、大数据集可用性的平行发展,以及更多的发展,极大地扩展了心律失常诊断、风险评估和治疗的应用。基于大数据的更精确算法、个性化风险评估、远程医疗和移动健康、智能硬件和可穿戴设备,以及对罕见或复杂类型心律失常的探索是未来的方向。