This paper deals with the extraction of the coronary network on dynamic volume sequences, acquired in multi-slice spiral computed tomography (MSCT). The proposed approach makes use of a tracking algorithm of the vascular structure, combining a 3D geometric moment operator with a multiscale Hessian filter to estimate the vessel central axis location, its local diameter and orientation. The method performs at the same time, a bifurcation detection to reconstitute the structure of the coronary network. The mean computation time to extract a coronary network is about 3 minutes using a P4-2.4G PC. Preliminary encouraging results are presented on one volume of a sequence.
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http://dx.doi.org/10.1109/IEMBS.2006.260712 | DOI Listing |
J Med Internet Res
January 2025
Department of Gastroenterology, Affiliated Hospital of Guangdong Medical University, Zhanjiang, China.
Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.
Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.
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 PDFASAIO J
January 2025
Departments of Surgery and Pediatrics, Congenital Heart Center, University of Florida, Gainesville, Florida.
This Extracorporeal Life Support Organization guideline describes early rehabilitation or mobilization of patients on extracorporeal membrane oxygenation (ECMO). The guideline describes useful and safe practices put together by an international interprofessional team with extensive experience in the field of ECMO and ECMO rehabilitation or mobilization. The guideline is not intended to define the delivery of care or substitute sound clinical judgment.
View Article and Find Full Text PDFPLoS 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.
View Article and Find Full Text PDFPLoS One
January 2025
College of Education for the Future, Beijing Normal University, Zhuhai, Guangdong, China.
Personalized sports training plans are essential for addressing individual athlete needs, but traditional methods often need to integrate diverse data types, limiting adaptability and effectiveness. Existing machine learning (ML) and rule-based approaches cannot dynamically generate context-specific training programs, reducing their applicability in real-world scenarios. This study aims to develop a Generative Adversarial Network (GAN)- based framework to create context-specific training plans by integrating numeric attributes (e.
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