Download full-text PDF |
Source |
|---|
Publication Analysis
Top Keywords
Similar Publications
IntroductionAsthma attacks are set off by triggers such as pollutants from the environment, respiratory viruses, physical activity and allergens. The aim of this research is to create a machine learning model using data from mobile health technology to predict and appropriately warn a patient to avoid such triggers.MethodsLightweight machine learning models, XGBoost, Random Forest, and LightGBM were trained and tested on cleaned asthma data with a 70-30 train-test split.
View Article and Find Full Text PDFClassification of Severity of Lung Parenchyma Using Saliency and Discrete Cosine Transform Energy in Computed Tomography of Patients With COVID-19.
Int J Telemed Appl
January 2025
Medical Familiar Unit, Instituto de Seguridad y Servicios Sociales de Los Trabajadores del Estado, Torreón, Coahuila, Mexico.
This study proposes an automated system for assessing lung damage severity in coronavirus disease 2019 (COVID-19) patients using computed tomography (CT) images. These preprocessed CT images identify the extent of pulmonary parenchyma (PP) and ground-glass opacity and pulmonary infiltrates (GGO-PIs). Two types of images-saliency () image and discrete cosine transform (DCT) energy image-were generated from these images.
View Article and Find Full Text PDFOptimal extreme learning machine for diagnosing brain tumor based on modified sailfish optimizer.
Heliyon
July 2024
College of Engineering and IT, University of Dubai, Academic City, 14143, Dubai, United Arab Emirates.
This study proposes a hierarchical automated methodology for detecting brain tumors in Magnetic Resonance Imaging (MRI), focusing on preprocessing images to improve quality and eliminate artifacts or noise. A modified Extreme Learning Machine is then used to diagnose brain tumors that are integrated with the Modified Sailfish optimizer to enhance its performance. The Modified Sailfish optimizer is a metaheuristic algorithm known for efficiently navigating optimization landscapes and enhancing convergence speed.
View Article and Find Full Text PDFOnline videos are a popular medium for science communication. These videos can be presented from many perspectives, including scientists sharing their own work or a third-party presenting research findings. A mixed between- and within-subjects experiment ( = 620) was conducted in the United States to assess the impact of narrative perspective on the communication objectives of increasing knowledge, changing perceptions, and influencing behavior related to bee diversity.
View Article and Find Full Text PDFEpisodic and associative memory from spatial scaffolds in the hippocampus.
Nature
January 2025
Department of Brain and Cognitive Sciences and McGovern Institute, MIT, Cambridge, MA, USA.
Hippocampal circuits in the brain enable two distinct cognitive functions: the construction of spatial maps for navigation, and the storage of sequential episodic memories. Although there have been advances in modelling spatial representations in the hippocampus, we lack good models of its role in episodic memory. Here we present a neocortical-entorhinal-hippocampal network model that implements a high-capacity general associative memory, spatial memory and episodic memory.
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!