Results 61 to 70 of about 3,957 (194)

Informationization Design of College English Corpus Using Deep Learning Algorithms

Journal of Applied Science and Engineering
This study proposes the ISSO-SNN model for semantic readability assessment in a college English corpus, addressing limitations of traditional methods. Using NLP preprocessing and TF-IDF features, the model leverages a Siamese network optimized with ISSO ...
Cheng Lin, Ruixue Li
doaj   +1 more source

Deep Spatial-Temporal Joint Feature Representation for Video Object Detection

Sensors, 2018
With the development of deep neural networks, many object detection frameworks have shown great success in the fields of smart surveillance, self-driving cars, and facial recognition. However, the data sources are usually videos, and the object detection
Baojun Zhao, Boya Zhao, Linbo Tang, Yuqi Han, Wenzheng Wang   +4 more
doaj   +1 more source

The gut microbiome organ

iMeta, EarlyView.
The gut microbiome can be conceptualized as a distributed organ‐like functional system with spatially structured organization, broad biochemical capacity, and continuous bidirectional communication with the host. By transforming dietary, host‐derived, and environmental substrates into bioactive metabolites with endocrine‐like, immunomodulatory, and ...
Yang Bi, Weibin Song, Maria Glymenaki, Jie Hu, Xiru Li, Heng Huang, Yousong Peng, Shuaishuai Ni, Ornuma Haonon, Zhu Liu, Krai Daowtak, Xiaotao Shen, Huadong Peng, Jutarop Phetcharaburanin, Huiru Tang, Yulan Wang, Jia V. Li, Mizu Jiang, Nick Powell, Victor W. Zhong, Elaine Holmes, Yunlei Xianyu, Zhigang Liu   +22 more
wiley   +1 more source

Building Damage Assessment Using Feature Concatenated Siamese Neural Network

IEEE Access
Fast and accurate post-earthquake building damage assessment is an important task to do to define search and rescue procedures. Many approaches have been proposed to automate this process by using artificial intelligence, some of which use handcrafted ...
Mgs M. Luthfi Ramadhan, Grafika Jati, Wisnu Jatmiko   +2 more
doaj   +1 more source

Local Descriptor Learning for Change Detection in Synthetic Aperture Radar Images via Convolutional Neural Networks

IEEE Access, 2019
In this paper, we present a novel convolutional neural network (CNN)-based model for change detection in synthetic aperture radar (SAR) images. Considering that change detection task takes image pairs as an input, we first explore multiple neural network
Huihui Dong, Wenping Ma, Yue Wu, Maoguo Gong, Licheng Jiao   +4 more
doaj   +1 more source

Optimizing Laboratory Autoverification in Complete Blood Count Testing Using Machine Learning: A Performance Evaluation Study

Journal of Clinical Laboratory Analysis, EarlyView.
This cross‐sectional study evaluated the feasibility of applying machine learning for complete blood count autoverification. Among 63,201 CBC results, the XGBoost model achieved higher sensitivity and predictive values compared with the traditional rule‐based system. ABSTRACT Background Autoverification improves laboratory efficiency by reducing manual
Sinsorn Srirujee, Peempol Chokchaipermpoonphol   +1 more
wiley   +1 more source

Speckle Noise Reduction in OCT Retinal Images Based on a Multi-Scale Self-Attention Generative Adversarial Network

Photonics
Optical coherence tomography (OCT) is widely used in biomedical imaging and ophthalmology. However, OCT images are frequently corrupted by speckle noise from coherent light interference.
Haiyi Bian, Yingzhou Zhu, Yeman Liu, Lei Liu, Xiaoteng Yan, Zhongjie Cheng, Yanrong Wang   +6 more
doaj   +1 more source

Promises and limitations of deep learning for predicting knee osteoarthritis progression from medical imaging: A systematic review

Knee Surgery, Sports Traumatology, Arthroscopy, EarlyView.
Abstract Purpose To systematically evaluate the performance, methodological quality, and translational barriers of deep learning (DL) models for predicting knee osteoarthritis (KOA) progression from medical imaging. Methods Following PRISMA guidelines, we searched PubMed, Scopus, and Web of Science (inception to June 2026) for peer‐reviewed studies ...
Amna Gillani, Rüdiger von Eisenhart‐Rothe, Klaus Woertler, Michael T. Hirschmann, Daniel Rueckert, Florian Hinterwimmer   +5 more
wiley   +1 more source

A Siamese ResNeXt network for predicting carotid intimal thickness of patients with T2DM from fundus images

Frontiers in Endocrinology
ObjectiveTo develop and validate an artificial intelligence diagnostic model based on fundus images for predicting Carotid Intima-Media Thickness (CIMT) in individuals with Type 2 Diabetes Mellitus (T2DM).MethodsIn total, 1236 patients with T2DM who had ...
AJuan Gong, Wanjin Fu, Heng Li, Na Guo, Tianrong Pan   +4 more
doaj   +1 more source

Living with the Unknown: Intolerance of Uncertainty in Parkinson's Disease

Movement Disorders Clinical Practice, EarlyView.
Abstract Background Parkinson's disease (PD) is marked by pervasive uncertainty due to fluctuating motor and non‐motor symptoms, variable treatment response, and an unpredictable clinical course. Intolerance of uncertainty (IU), a tendency to perceive ambiguity as threatening and respond with worry, avoidance, or decisional paralysis, may be ...
Bradley McDaniels, Gregory M. Pontone, Kuhan Pushparatnam, Indu Subramanian   +3 more
wiley   +1 more source