Atrial Fibrillation Recurrence Estimation

Atrial Fibrillation Recurrence Estimation is a predictive model based on big data and machine learning technologies, designed to assess the risk of recurrence in patients with atrial fibrillation. The model provides precise predictions of recurrence probability by analyzing the patient's clinical data, ECG characteristics, and historical disease course, helping doctors to develop personalized treatment plans and management strategies, thereby effectively reducing the recurrence rate and improving the patient's quality of life and prognosis.