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Mehrabi Nasab E, Sadeghian S, Vasheghani Farahani A, Yamini Sharif A, Masoud Kabir F, Bavanpour Karvane H, Zahedi A, Bozorgi A. Determining the recurrence rate of premature ventricular complexes and idiopathic ventricular tachycardia after radiofrequency catheter ablation with the help of designing a machine-learning model. Regen Ther 2024; 27:32-38. [PMID: 38496010 PMCID: PMC10940794 DOI: 10.1016/j.reth.2024.03.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/27/2024] [Revised: 02/28/2024] [Accepted: 03/03/2024] [Indexed: 03/19/2024] Open
Abstract
Ventricular arrhythmias increase cardiovascular morbidity and mortality. Recurrent PVCs and IVT are generally considered benign in the absence of structural heart abnormalities. Artificial intelligence is a rapidly growing field. In recent years, medical professionals have shown great interest in the potential use of ML, an integral part of AI, in various disciplines, including diagnostic applications, decision-making, prognostic stratification, and solving complex pathophysiological aspects of diseases from these data at extraordinary complexity, scale, and acquisition rate. The aim of this study was to design an ML model to predict the probability of PVC and IVT recurrence after RF ablation. Data of patients were collected and manipulated using traditional analysis and various artificial intelligence models, namely MLP, Gradient Boosting Machines, Random Forest, and Logistic Regression. Hypertension, male sex, and the use of non-irrigate catheters were associated with less freedom from arrhythmia. All these results were obtained through traditional analytic methods, and according to AI, none of the variables had a clear effect on the recurrence of arrhythmia. Each AI model presents unique strengths and weaknesses, and further optimization and fine-tuning of these models are necessary to increase their clinical utility. By expanding the dataset, improved predictions can be fostered to ultimately increase the clinical utility of AI in predicting PVC erosion outcomes.
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Affiliation(s)
- Entezar Mehrabi Nasab
- Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
- Department of Cardiology, School of Medicine, Valiasr Hospital, Zanjan University of Medical Sciences, Zanjan, Iran
| | - Saeed Sadeghian
- Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Ali Vasheghani Farahani
- Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Ahmad Yamini Sharif
- Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | - Farzad Masoud Kabir
- Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
| | | | - Ahora Zahedi
- Department of Artificial Intelligence in Medical Sciences, Faculty of Advanced Technologies in Medicine, Iran University of Medical Sciences, Tehran, Iran
| | - Ali Bozorgi
- Department of Cardiology, School of Medicine, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran
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Calvert P, Mills MT, Gupta D. Duration of atrial fibrillation: How much is too much? Heart Rhythm 2024; 21:741-742. [PMID: 38336195 DOI: 10.1016/j.hrthm.2024.01.057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/26/2024] [Revised: 01/29/2024] [Accepted: 01/30/2024] [Indexed: 02/12/2024]
Affiliation(s)
- Peter Calvert
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool, United Kingdom; Liverpool Heart & Chest Hospital NHS Foundation Trust, Liverpool, United Kingdom
| | - Mark T Mills
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool, United Kingdom; Liverpool Heart & Chest Hospital NHS Foundation Trust, Liverpool, United Kingdom
| | - Dhiraj Gupta
- Liverpool Centre for Cardiovascular Science at University of Liverpool, Liverpool, United Kingdom; Liverpool Heart & Chest Hospital NHS Foundation Trust, Liverpool, United Kingdom.
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