Cardiovascular Topic
Yazarlar (6)
Dr. Öğr. Üyesi Erhan Arıkan Bilecik Şeyh Edebali Üniversitesi, Türkiye
Dr. Öğr. Üyesi Faik Özel Bilecik Şeyh Edebali Üniversitesi, Türkiye
Ramazan Aslan Bilecik Şeyh Edebali Üniversitesi, Türkiye
Prof. Dr. Murat Özmen Atatürk Üniversitesi, Türkiye
Arş. Gör. Ahmet ARDAHANLI Kafkas Üniversitesi, Türkiye
Isa Ardahanlı
Bilecik Şeyh Edebali Üniversitesi, Türkiye
Bilecik Şeyh Edebali Üniversitesi, Türkiye
| Makale Türü | Özgün Makale (SSCI, AHCI, SCI, SCI-Exp dergilerinde yayınlanan tam makale) | ||
| Dergi Adı | Cardiovasc J Afr (Q4) | ||
| Dergi Tarandığı Indeksler | |||
| Makale Dili | İngilizce | Basım Tarihi | 01-2025 |
| Cilt / Sayı / Sayfa | 36 / 0 / 491–498 | DOI | – |
| Makale Linki | https://www.researchgate.net/profile/Isa-Ardahanli/publication/396947438_Rapid_AI-assisted_Poincare_plot_analysis_for_early_detection_of_subclinical_left_ventricular_dysfunction_in_hypertensive_patients_admitted_to_the_emergency_department_A_prospect | ||
| UAK Araştırma Alanları |
Bilgisayar Bilimleri ve Mühendisliği
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| Özet |
| Introduction: Early detection of subclinical left ventricular (LV) dysfunction in hypertensive patients presenting to the emergency department (ED) is of critical importance. We aimed to evaluate the performance of artificial intelligence (AI)-assisted Poincaré plot analysis of electrocardiogram (ECGs) to identify subclinical LV dysfunction rapidly. Methods: 60 hypertensive patients and 55 normotensive controls were prospectively enrolled in the ED. After stabilisation, all participants underwent 5-minute ECG recordings. Heart rate variability (HRV) measurements were calculated, and Poincaré plots were generated. A convolutional neural network (CNN) model was trained to classify the Poincaré plot images. Transthoracic echocardiography was performed within 24 hours to measure left ventricular ejection fraction (LVEF) and |
| Anahtar Kelimeler |
