Clustering Analysis of Long-term Cardiovascular Complications in COVID-19 Patients
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arXiv
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| Main Authors: | , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866910900184678400 |
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| author | Sadegh-Zadeh, Seyed Ali Mamalo, Alireza Soleimani Behnemoon, Mahsa Ojarudi, Masoud Gharebaghi, Naser Pashaei, Mohammad Reza |
| author_facet | Sadegh-Zadeh, Seyed Ali Mamalo, Alireza Soleimani Behnemoon, Mahsa Ojarudi, Masoud Gharebaghi, Naser Pashaei, Mohammad Reza |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_00007 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Clustering Analysis of Long-term Cardiovascular Complications in COVID-19 Patients Sadegh-Zadeh, Seyed Ali Mamalo, Alireza Soleimani Behnemoon, Mahsa Ojarudi, Masoud Gharebaghi, Naser Pashaei, Mohammad Reza Quantitative Methods Applications 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. |
| title | Clustering Analysis of Long-term Cardiovascular Complications in COVID-19 Patients |
| topic | Quantitative Methods Applications |
| url | https://arxiv.org/abs/2504.00007 |