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Probabilistic learning of the Purkinje network from the electrocardiogram.
Med Image Anal
January 2025
Department of Mechanical and Metallurgical Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile; Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile; Millennium Institute for Intelligent Healthcare Engineering, iHEALTH, Chile. Electronic address:
The identification of the Purkinje conduction system in the heart is a challenging task, yet essential for a correct definition of cardiac digital twins for precision cardiology. Here, we propose a probabilistic approach for identifying the Purkinje network from non-invasive clinical data such as the standard electrocardiogram (ECG). We use cardiac imaging to build an anatomically accurate model of the ventricles; we algorithmically generate a rule-based Purkinje network tailored to the anatomy; we simulate physiological electrocardiograms with a fast model; we identify the geometrical and electrical parameters of the Purkinje-ECG model with Bayesian optimization and approximate Bayesian computation.
View Article and Find Full Text PDFClozapine for Treatment-Resistant Disruptive Behaviors in Youths With Autism Spectrum Disorder Aged 10-17 Years: Protocol for an Open-Label Trial.
JMIR Res Protoc
January 2025
Graduate Program of Psychiatry and Behavioral Sciences, Department of Psychiatry, Federal University of Rio Grande do Sul (UFRGS), Porto Alegre, Brazil.
Background: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition emerging in early childhood, characterized by core features such as sociocommunicative deficits and repetitive, rigid behaviors, interests, and activities. In addition to these, disruptive behaviors (DB), including aggression, self-injury, and severe tantrums, are frequently observed in pediatric patients with ASD. The atypical antipsychotics risperidone and aripiprazole, currently the only Food and Drug Administration-approved treatments for severe DB in patients with ASD, often encounter therapeutic failure or intolerance.
View Article and Find Full Text PDFA comparative analysis of CNNs and LSTMs for ECG-based diagnosis of arrythmia and congestive heart failure.
Comput Methods Biomech Biomed Engin
January 2025
Centre for Research Impact & Outcome, Chitkara University Institute of Engineering and Technology, Chitkara University, Rajpura, Punjab, India.
Cardiac arrhythmias are major global health concern and their early detection is critical for diagnosis. This study comprehensively evaluates the effectiveness of CNNs and LSTMs for the classification of cardiac arrhythmias, considering three PhysioNet datasets. ECG records are segmented to accommodate around ∼10s of ECG data.
View Article and Find Full Text PDFRight Ventricular Myocardial Infarction: Pathophysiology, Diagnosis, and Therapeutic Approaches.
Cardiol Rev
January 2025
Departments of Cardiology and Medicine, New York Medical College and Westchester Medical Center, Valhalla, NY.
Right ventricular myocardial infarction (RVMI) is a significant and distinct form of acute myocardial infarction associated with considerable morbidity and mortality. It occurs most commonly due to proximal right coronary artery obstruction, often in conjunction with inferior myocardial infarction. RVMI poses unique diagnostic and therapeutic challenges due to the anatomical and functional differences between the right and left ventricles.
View Article and Find Full Text PDFImproving myocardial infarction diagnosis with Siamese network-based ECG analysis.
PLoS One
January 2025
School of Computer Science & Engineering (SCOPE), VIT-AP University, Amaravati, Andhra Pradesh, India.
Background: Heart muscle damage from myocardial infarction (MI) is brought on by insufficient blood flow. The leading cause of death for middle-aged and older people worldwide is myocardial infarction (MI), which is difficult to diagnose because it has no symptoms. Clinicians must evaluate electrocardiography (ECG) signals to diagnose MI, which is difficult and prone to observer bias.
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