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| http://dx.doi.org/10.1136/hrt.40.3.315 | DOI Listing |
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A Belgian physician-initiated trial investigating the LifeStream peripheral stent graft system for the treatment of complex TASC C and D iliac lesions.
J Cardiovasc Surg (Torino)
February 2025
Department of Vascular Surgery, AZ Sint Blasius, Dendermonde, Belgium.
Background: Due to the heterogeneity of literature findings, stent type selection for the endovascular treatment of complex aorto-iliac occlusive disease remains challenging. The BELSTREAM study, a physician-initiated, prospective, multicenter, single-arm study, aims to report the safety and efficacy of the balloon expandable LifeStream Peripheral Stent Graft System (BD, Tempe, Arizona, USA) for the treatment of complex TASC C and D aorto-iliac artery lesions.
Methods: Seventy patients and 133 lesions were included at six Belgian institutions.
Dilated SE-DenseNet for brain tumor MRI classification.
Sci Rep
January 2025
Department of Applied Mathematics, University of Waterloo, Waterloo, ON, N2L 3G1, Canada.
In the field of medical imaging, particularly MRI-based brain tumor classification, we propose an advanced convolutional neural network (CNN) leveraging the DenseNet-121 architecture, enhanced with dilated convolutional layers and Squeeze-and-Excitation (SE) networks' attention mechanisms. This novel approach aims to improve upon state-of-the-art methods of tumor identification. Our model, trained and evaluated on a comprehensive Kaggle brain tumor dataset, demonstrated superior performance over established convolution-based and transformer-based models: ResNet-101, VGG-19, original DenseNet-121, MobileNet-V2, ViT-L/16, and Swin-B across key metrics: F1-score, accuracy, precision, and recall.
View Article and Find Full Text PDFExamining Mammalian facial behavior using Facial Action Coding Systems (FACS) and combinatorics.
PLoS One
January 2025
Department of Psychology, Lyon College, Batesville, Arkansas, United States of America.
There has been an increased interest in standardized approaches to coding facial movement in mammals. Such approaches include Facial Action Coding Systems (FACS), where individuals are trained to identify discrete facial muscle movements that combine to create a facial configuration. Some studies have utilized FACS to analyze facial signaling, recording the quantity of morphologically distinct facial signals a species can generate.
View Article and Find Full Text PDFEvaluation of the Adhesion Strength of Ultrathin Gold Coatings on Substrates of Soda-Lime Glass and Cyclo-Olefin-Polymer by Cross-Cut and Scratch Tests under the Influence of a Thermal Shock Test for Use in Biosensors.
ACS Omega
January 2025
Institute for Micro Integration (IFM), University of Stuttgart, Allmandring 9B, 70569 Stuttgart, Germany.
The current demand for highly sensitive, optical sensors in biodiagnostics has prompted the development of ultrathin metal coatings on a range of substrates. Given the potential attenuation of the signal from a plasmonic sensor for the detection of fluorescent molecules when an adhesion layer between the substrate and coating is employed, this study examines the impact of various factors on the adhesion strength between gold coatings and substrates comprising glass and cyclo-olefin-polymer (COP). The objective is to identify potential configurations for high adhesion strength, thereby eliminating the need for an adhesion layer in the fabrication of optical sensors with gold coatings for diagnostic applications or to utilize a minimal adhesion layer thickness.
View Article and Find Full Text PDFColorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach.
Sci Rep
January 2025
Ministry of Higher Education, Mataria Technical College, Cairo, 11718, Egypt.
The current work introduces the hybrid ensemble framework for the detection and segmentation of colorectal cancer. This framework will incorporate both supervised classification and unsupervised clustering methods to present more understandable and accurate diagnostic results. The method entails several steps with CNN models: ADa-22 and AD-22, transformer networks, and an SVM classifier, all inbuilt.
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