ArticleBalkan medical journal2026
A Multimodular AI Algorithm for Automated Assessment of Left Ventricular Function in Ischemic Heart Disease: Ejection Fraction, Wall Motion, and Regional Myocardial Segmentation.
Article in Balkan medical journal, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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8 authors.
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Abstract
Background: Ischemic heart damage reduces the pumping efficiency of the heart by affecting the left ventricular ejection fraction (LVEF) and causing wall motion abnormality (WMA). In daily clinical practice, these parameters are interpreted by physicians using two dimensional transthoracic echocardiography (2D-TTE). Because 2D-TTE reports rely on visual evaluations, they are subject to experience-based limitations and exhibit low reproducibility. Aims: To develop an artificial intelligence algorithm composed of two modules that enable automatic LVEF calculation and WMA detection for analyzing 2D-TTE images. Study Design: Diagnostic accuracy study. Methods: A total of 600 adult patients were retrospectively included. The model combined static frame segmentation with dynamic tracking using a hybrid Simpson's method applied to apical 2- and 4-chamber views. Model performance was assessed against cardiologist measurements using Bland-Altman analysis. The YOLOv8 and ResNet50 models were employed for the wall motion module. Performance metrics, including accuracy, precision, F1 score, and area under the curve, were evaluated. Results: In the Bland-Altman analysis, the mean bias between the LVEF module and cardiologist measurements was -4, with limits of agreement ranging from -15 to -3. Regression analysis demonstrated a strong correlation between the LVEF module and cardiologist measurements (r = 0.71, Conclusion: This is the first study to integrate automated EF calculation and WMA detection within a single workflow. SafeHeart offers accurate, reproducible, and rapid analysis, with the potential to support routine echocardiography practice. Color-coded region segmentation can facilitate more standardized and reliable results. Sidem Gül1, Reşit Taşdemir2, Beyza Açıkgöz2, Hakan Duman3, Hamza Hodzic4, Sena Köker5, Nazlı Erdemir6, Mehmet Kıvrak7 Corresponding.
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