Early and accurate prediction of neurological outcomes in comatose patients following cardiac arrest is critical for informed clinical decision-making. Existing studies have predominantly focused on EEG for assessing brain injury, with some exploring...
IEEE transactions on biomedical circuits and systems
Apr 3, 2025
Many electrocardiogram (ECG) processors have been widely used for cardiac monitoring. However, most of them have relatively low energy efficiency, and lack configurability in classification leads number and inference algorithm models. A multi-lead EC...
Long QT syndrome (LQTS) presents a group of inheritable channelopathies with prolonged ventricular repolarization, leading to syncope, ventricular tachycardia, and sudden death. Differentiating LQTS genotypes is crucial for targeted management and tr...
This pilot study evaluates an artificial intelligence (AI)-assisted electrocardiography (ECG) analysis system, QCG, to enhance urgent coronary angiography (CAG) decision-making for acute chest pain in the emergency department (ED). We retrospectively...
BACKGROUND: Atrial fibrillation (AF) is a common but often undiagnosed condition, increasing the risk of stroke and heart failure. Early detection is crucial, yet traditional methods struggle with AF's transient nature. This study investigates how au...
Critical care nursing clinics of North America
Mar 26, 2025
The systematic annotation of crisis alarms reveals a high number of false alarms for both ventricular tachycardia and asystole, which are best identified by inspecting simultaneous multilead electrocardiographs. Among the few true crisis alarms, 11 w...
Electrocardiogram (ECG) datasets tend to be highly imbalanced due to the scarcity of abnormal cases. Additionally, the use of real patients' ECGs is highly regulated due to privacy issues. Therefore, there is always a need for more ECG data, especial...
Chagas disease (CD), caused by the protozoan parasite Trypanosoma cruzi (T. cruzi), represents a major public health concern in most of the American continent and causes 12,000 deaths every year. CD clinically manifests in two phases (acute and chron...
IEEE transactions on bio-medical engineering
Mar 21, 2025
This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) methods. Our objective is to enhance the accuracy and robustness of ECGI reconstructions. We reshape the ...
The availability of large-scale electrocardiogram (ECG) databases and advancements in machine learning have facilitated the development of automated diagnostic systems for cardiac arrhythmias. Deep learning models, despite their potential for high ac...
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