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http://dx.doi.org/10.4070/kcj.2013.43.11.782 | DOI Listing |
JACC Adv
January 2025
Telfer School of Management, University of Ottawa, Ottawa, Ontario, Canada.
JACC Adv
January 2025
Department of Radiology, Mayo Clinic, Phoenix, Arizona, USA.
Background: Immune checkpoint inhibitor (ICI) therapy has dramatically improved the prognosis for some cancers but can be associated with myocarditis, adverse cardiovascular events, and mortality.
Objectives: The aim of this study was to develop an artificial intelligence (AI) model to predict the increased likelihood for the development of ICI-related myocarditis and adverse cardiovascular events.
Methods: Cancer patients treated with ICI at a tertiary institution from 2011 to 2022 were reviewed.
Curr Cardiol Rep
January 2025
Division of Cardiology, McGill University Health Centre, 845 Rue Sherbrooke O, Montreal, QC, H3H 0G4, Canada.
Purpose Of Review: This review aims to evaluate current diagnostic and therapeutic strategies for postpericardiotomy syndrome (PPS), with a focus on the evolving role of multimodality imaging, including echocardiography, cardiac computed tomography (CCT), and cardiac magnetic resonance imaging (CMR). The review also explores the potential benefits of advanced imaging in improving the accuracy and management of PPS.
Recent Findings: PPS, a common complication following cardiac surgery, presents with pleuritic chest pain, fever, and pericardial or pleural effusion.
Med Biol Eng Comput
January 2025
Department of Computer Science and Engineering, Shri Shankaracharya Institute of Professional Management and Technology, Raipur, (C.G.), India.
This study presents an advanced methodology for 3D heart reconstruction using a combination of deep learning models and computational techniques, addressing critical challenges in cardiac modeling and segmentation. A multi-dataset approach was employed, including data from the UK Biobank, MICCAI Multi-Modality Whole Heart Segmentation (MM-WHS) challenge, and clinical datasets of congenital heart disease. Preprocessing steps involved segmentation, intensity normalization, and mesh generation, while the reconstruction was performed using a blend of statistical shape modeling (SSM), graph convolutional networks (GCNs), and progressive GANs.
View Article and Find Full Text PDFACS Nano
January 2025
School of Mechanical and Manufacturing Engineering, University of New South Wales, Sydney, New South Wales 2052, Australia.
Implantable systems with chronic stability, high sensing performance, and extensive spatial-temporal resolution are a growing focus for monitoring and treating several diseases such as epilepsy, Parkinson's disease, chronic pain, and cardiac arrhythmias. These systems demand exceptional bendability, scalable size, durable electrode materials, and well-encapsulated metal interconnects. However, existing chronic implantable bioelectronic systems largely rely on materials prone to corrosion in biofluids, such as silicon nanomembranes or metals.
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