CORTEXA
← Browse
zenodoConference paper2025-05-29

Economic Evaluation of Heart Failure Strategies in the STRATIFYHF Project

Marija Gacic, Milica Kaplarevic, Lazar Velicki, Djordje Jakovljevic, Nenad Filipovic

The STRATIFYHF project develops an AI-based decision support system integrating patient data with computational modelling to support risk stratification, diagnosis and progression prediction in heart failure. This study evaluates the cost-effectiveness of AI-enhanced ECG screening for asymptomatic left ventricular dysfunction in Serbia using decision-tree and Markov modelling. Screening at age 65 was estimated to cost around \$23,351 per quality-adjusted life year (QALY) gained, below the common \$30,000 willingness-to-pay threshold, with comparable results at ages 55 and 75. The analysis highlights that cost-effectiveness is highly sensitive to test performance and screening costs, motivating further validation of the AI algorithm. This work was presented at the 4th Serbian International Conference on Applied Artificial Intelligence (SICAAI 2025), Zlatibor, Serbia, and was carried out within the STRATIFYHF project.

View free PDFSource page

Related papers

zenodoConference paper2026-07-28

KeepA(n)I: Social Stereotypes in and Social Norms for Computer Vision

Evgenia Christoforou, Nicolas Nicolaou, Efstathios Stavrakis, Jahna Otterbacher

The KeepA(n)I platform facilitates the auditing of computer vision systems that tag images, which aid visual communication on the Web and social media, from content moderation to the development of new apps and tools. In particular, KeepA(n)I enables a broad set of stakeholders t…

View free PDFSource page
zenodoConference paper2026-07-28

Self-Supervised Relevance Modelling in Autonomous Driving via Counterfactual Analysis

Luca Lusvarghi, Javier Gozalvez, Pablo Urbano Hidalgo

Autonomous driving relies on computationally intensive perception pipelines to continuously detect and track objects in the surrounding environment. While some objects are key to plan safe and effective maneuvers, others may not be relevant and have no impact on the autonomous ve…

View free PDFSource page
zenodoConference paper2026-05-27

Обмеження навчання моделей комп'ютерного зору для систем розпізнавання психоемоційних станів в авіаційній інфраструктурі

Наталія Подопригора

У статті досліджуються епістемологічні та алгоритмічні обмеження сучасних моделей комп'ютерного зору (зокрема архітектури YOLOv8) щодо автоматизованого розпізнавання складних психоемоційних станів в умовах авіаційної інфраструктури. На основі трансдисциплінарної методології…

View free PDFSource page
zenodoConference paper2026-05-20

SoC-Based Implementation of CNN Model for End-Diastolic Volume Classification from Echocardiogram via hls4ml

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…

View free PDFSource page
zenodoConference paper2026-05-20

Comparative Analysis of U-Net-Based Architectures for Coronary Artery Segmentation Using X-Ray Angiography Images

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…

View free PDFSource page