Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4645791 | PMC |
Publication Analysis
Top Keywords
Similar Publications
Development and Validation of a Model Based on Circulating Biomarkers for Discriminating Symptomatic Spontaneous Intracranial Artery Dissection.
Transl Stroke Res
January 2025
Department of Neurosurgery, Shanxi Provincial People's Hospital, Taiyuan, Shanxi, China.
Spontaneous intracranial artery dissection (sIAD) is the leading cause of stroke in young individuals. Identifying high-risk sIAD cases that exhibit symptoms and are likely to progress is crucial for treatment decision-making. This study aimed to develop a model relying on circulating biomarkers to discriminate symptomatic sIADs.
View Article and Find Full Text PDFComparative analysis of Ball Mapper and conventional Mapper in investigating air pollutants' behavior.
Environ Monit Assess
January 2025
School of Mathematical Sciences, Universiti Sains Malaysia, 11800 USM, Penang, Malaysia.
This study investigates the effectiveness and efficiency of two topological data analysis (TDA) techniques, the conventional Mapper (CM) and its variant version, the Ball Mapper (BM), in analyzing the behavior of six major air pollutants (NO, PM, PM, O, CO, and SO) across 60 air quality monitoring stations in Malaysia. Topological graphs produced by CM and BM reveal redundant monitoring stations and geographical relationships corresponding to air pollutant behavior, providing better visualization than traditional hierarchical clustering. Additionally, a comparative analysis of topological graph structures was conducted using node degree distribution, topological graph indices, and Dynamic Time Warping (DTW) to evaluate the sensitivity and performance of these TDA techniques.
View Article and Find Full Text PDFEnhancing percutaneous coronary intervention using TriVOCTNet: a multi-task deep learning model for comprehensive intravascular optical coherence tomography analysis.
Phys Eng Sci Med
January 2025
Faculty of Engineering, Department of Biomedical Engineering, Universiti Malaya, Kuala Lumpur, Malaysia.
Neointimal coverage and stent apposition, as assessed from intravascular optical coherence tomography (IVOCT) images, are crucial for optimizing percutaneous coronary intervention (PCI). Existing state-of-the-art computer algorithms designed to automate this analysis often treat lumen and stent segmentations as separate target entities, applicable only to a single stent type and overlook automation of preselecting which pullback segments need segmentation, thus limit their practicality. This study aimed for an algorithm capable of intelligently handling the entire IVOCT pullback across different phases of PCI and clinical scenarios, including the presence and coexistence of metal and bioresorbable vascular scaffold (BVS), stent types.
View Article and Find Full Text PDFFrom Genes to Metabolites: HSP90B1's Role in Alzheimer's Disease and Potential for Therapeutic Intervention.
Neuromolecular Med
January 2025
Department of Neurology, Second Affiliated Hospital of Army Medical University (Xinqiao Hospital), Chongqing, China.
Alzheimer's disease (AD) is a prototypical neurodegenerative disorder, predominantly affecting individuals in the presenile and elderly populations, with an etiology that remains elusive. This investigation aimed to elucidate the alterations in anoikis-related genes (ARGs) in the AD brain, thereby expanding the repertoire of biomarkers for the disease. Using publically available gene expression data for the hippocampus from both healthy and AD subjects, differentially expressed genes (DEGs) were identified.
View Article and Find Full Text PDFEstimating body weight in Sujiang pigs using artificial neural network, nearest neighbor, and CART algorithms: a comparative study using morphological measurements.
Trop Anim Health Prod
January 2025
Faculty of Agriculture, Department of Animal Science, Isparta University of Applied Sciences, Isparta, Türkiye.
The objectives of this study were to evaluate different machine learning algorithms for predicting body weight (BW) in Sujiang pigs using the following morphological traits: age, body length (BL), backfat thickness (BFT), chest circumference (CC), body height (BH), chest width (CW), and hip width (HW). Additionally, this study also investigated which machine learning algorithms could accurately and efficiently predict body weight in pigs using a limited set of morphological traits. For this purpose, morphological measurements of 365 mature (180 ± 5 days) Sujiang pigs from the Jiangsu Sujiang Pig Breeding Farm in Taizhou, Jiangsu Province, China were used.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!