11 papers indexed
Filip Filipović, Tijana Geroski, N Filipovic
Coronary artery disease is one of the leading causes of morbidity and mortality worldwide, with X-ray coronary angiography serving as the clinical gold standard for diagnosis and intervention planning. Accurate segmentation of coronary arteries is essential for quantitative analy…
Filip Filipović, Tijana Geroski, N Filipovic
Coronary artery disease is one of the leading causes of morbidity and mortality worldwide, with X-ray coronary angiography serving as the clinical gold standard for diagnosis and intervention planning. Accurate segmentation of coronary arteries is essential for quantitative analy…
Anđela Stojadinović, Tijana Geroski, Dajana Jovanović, Nenad Filipović
Accurate delineation of coronary arteries from X-ray angiography supports early identification of narrowing or blockages, but is complicated by low contrast and thin, branching vessel structures. This study compares three U-Net-based segmentation architectures — U-Net, U-Ne…
Nemanja Marković, Tijana Geroski, Emil Jovanov, Nenad Filipović
Echocardiographic assessment of End-Diastolic Volume (EDV) is central to identifying dilated cardiomyopathy, a major driver of heart failure. This paper presents a low-latency, edge-computing solution that deploys an 8-bit quantized, 50%-pruned CNN directly onto a Xilinx Artix-7…
Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević, Andrej Preveden, Aleksandra Milovančev, et al.
Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 su…
Anđela Stojadinović, Tijana Geroski, Dajana Jovanović, Nenad Filipović
Accurate delineation of coronary arteries from X-ray angiography supports early identification of narrowing or blockages, but is complicated by low contrast and thin, branching vessel structures. This study compares three U-Net-based segmentation architectures — U-Net, U-Ne…
Ognjen Pavić, Lazar Dašić, Tijana Geroski, Anđela Blagojević, Andrej Preveden, Aleksandra Milovančev, et al.
Accurate classification of echocardiographic views (e.g. apical 2- and 4-chamber, parasternal long-axis) is an important prerequisite for reliable ejection-fraction assessment and heart failure diagnosis, but manual classification is time-consuming. This study evaluates the EchoJ…
Lazar Dašić, Ognjen Pavić, Tijana Geroski, Anđela Blagojević, Andrej Preveden, Aleksandra Milovančev, et al.
Voice characteristics are an emerging, non-invasive biomarker for heart failure. This study develops a machine learning pipeline to differentiate patients with suspected heart failure from those with a confirmed diagnosis using vocal features alone, drawing on 240 patients (50 su…
Nemanja Marković, Tijana Geroski, Emil Jovanov, Nenad Filipović
Echocardiographic assessment of End-Diastolic Volume (EDV) is central to identifying dilated cardiomyopathy, a major driver of heart failure. This paper presents a low-latency, edge-computing solution that deploys an 8-bit quantized, 50%-pruned CNN directly onto a Xilinx Artix-7…
Tijana Geroski, Mahyar Bolhassani, Narayana S. Singam, Ayman Battisha, Nenad Filipović, Dinesh Kalra, et al.
Distinguishing heart failure with reduced ejection fraction (HFrEF) from heart failure with preserved ejection fraction (HFpEF) is clinically important but challenging. This paper presents an end-to-end deep learning pipeline for automated three-class classification (healthy, HFr…
Ognjen Pavić, Lazar Dašić, Anđela Blagojević, Tijana Geroski, Nenad Filipović
Heart failure and chronic obstructive pulmonary disease often present with overlapping clinical signs, making differential diagnosis challenging. This work applies machine learning, primarily random forest ensembles trained on heterogeneous clinical data (physical examination, bl…