Cardiovascular events prediction using artificial intelligence models and heart rate variability

M Moshawrab, M Adda, A Bouzouane, H Ibrahim… - Procedia Computer …, 2022 - Elsevier
Artificial Intelligence is exponentially evolving into a solution to many of humanity's complex
problems. In this context, healthcare is benefiting from this technology and all its branches to …

A Deep Learning Model for QRS Delineation in Organized Rhythms during In-Hospital Cardiac Arrest

J Urteaga, A Elola, D Herráez, A Norvik… - International Journal of …, 2025 - Elsevier
Background Cardiac arrest (CA) is the sudden cessation of heart function, typically resulting
in loss of consciousness and cessation of pulse and breathing. The electrocardiogram …

Completing the Cabrera Circle: deriving adaptable leads from ECG limb leads by combining constraints with a correction factor

H Dathe, D Krefting, N Spicher - Physiological Measurement, 2023 - iopscience.iop.org
Objective. We present a concept for processing 6-lead electrocardiography (ECG) signals
which can be applied to various use cases in quantitative electrocardiography. Approach …

[PDF][PDF] Predicting Cardiovascular Events with Machine Learning Models and Heart Rate Variability

M Moshawrab, M Adda, A Bouzouane… - Int. J. Ubiquitous Syst …, 2023 - researchgate.net
Artificial Intelligence (AI) is increasingly becoming a potential answer to many of science's
most challenging problems. In this context, healthcare is using this technology and its …

Machine Learning Models to Predict Cardiovascular Events from Heart Rate Variability Data

M Moshawrab, M Adda, A Bouzouane… - … on Human-Centric …, 2022 - ieeexplore.ieee.org
Among the diseases known to mankind, cardiovascular diseases remain the deadliest and
most expensive. However, Artificial Intelligence offers new solutions that can help diagnose …