Clustering Analysis of Long-term Cardiovascular Complications in COVID-19 Patients
Seyed Ali Sadegh-Zadeh, Alireza Soleimani Mamalo, Mahsa Behnemoon, Masoud Ojarudi, Naser Gharebaghi, Mohammad Reza Pashaei
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This study investigates long-term cardiovascular complications in COVID-19 patients using advanced clustering techniques. The objective was to analyse ECG parameters, demographic data, comorbidities, and hospitalization details to identify patterns in cardiovascular health outcomes. We applied K-means clustering and identified three distinct clusters: Cluster 0 with moderate heart rate variability and ICU admissions, Cluster 1 with lower heart rate variability and ICU admissions, and Cluster 2 with higher heart rate variability and ICU admissions, indicating higher risk profiles.