Predicting Early recurrence of atrial fibrilation post-catheter ablation using machine learning techniques.

Journal: BMC cardiovascular disorders
PMID: 39702028

Abstract

BACKGROUND: Catheter ablation is a common treatment for atrial fibrillation (AF), but recurrence rates remain variable. Predicting the success of catheter ablation is crucial for patient selection and management. This research seeks to create a machine learning model to forecast the early recurrence of atrial fibrillation following catheter ablation.

Authors

  • Amir Askarinejad
    Student research committee, Shiraz University of Medical Science, Shiraz, Iran.
  • Amirreza Sabahizadeh
    School of Medicine, Shiraz University of Medical Sciences, Shiraz, Iran.
  • Erfan Kohansal
    Rajaie Cardiovascular Medical and Research Institute, Iran university of medical sciences, Tehran, Iran.
  • Zahra Ghasemi
    Department of Business and Economy, Persian Gulf University, Bushehr, Iran.
  • Majid Haghjoo
    Department of Business and Economy, Persian Gulf University, Bushehr, Iran. majid.haghjoo@gmail.com.

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