Results 51 to 60 of about 67,072 (308)

Lung Disease Classification Using Deep Learning and ROI-Based Chest X-Ray Images

Technologies
Deep learning applied to chest X-ray (CXR) images has gained wide attention for its potential to improve diagnostic accuracy and accessibility in resource-limited healthcare settings.
Antonio Nadal-Martínez, Lidia Talavera-Martínez, Marc Munar, Manuel González-Hidalgo   +3 more
doaj   +1 more source

ANFIS-based soft computing models for forecasting effective drought index over an arid region of India [PDF]

, 2023
Ayilobeni Kikon, B. M. Dodamani, Surajit Deb Barma, Sujay Raghavendra Naganna   +3 more
openalex   +1 more source

Enzymatic degradation of biopolymers in amorphous and molten states: mechanisms and applications

FEBS Open Bio, EarlyView.
This review explains how polymer morphology and thermal state shape enzymatic degradation pathways, comparing amorphous and molten biopolymer structures. By integrating structure–reactivity principles with insights from thermodynamics and enzyme engineering, it highlights mechanisms that enable efficient polymer breakdown.
Anđela Pustak, Aleksandra Maršavelski
wiley   +1 more source

Upgrading ideas about the concept of Soft Computing [PDF]

International Journal of Computational Intelligence Systems, 2010
This short note is devoted to introduce the discussion carried out along this special issue on the concept of Soft Computing by key researchers in the field.
Javier Montero, Luis Martinez
doaj   +1 more source

Prediction Model for Etiologic Differentiation of Isolated Vestibular Syndrome in Emergency Settings

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective This study aimed to develop and validate a predictive model for differentiating central from peripheral etiologies in patients with isolated vestibular syndrome (VS). Methods In this multicenter retrospective cohort study, 506 patients with isolated VS from five hospitals were divided into derivation (n = 301) and validation (n = 205)
Guo Wenting, Du Liping, Yang Yi, Hu Jin, Ye Bijun, Wang Jianer, Liu Shuangsi, Guo Shunyuan, Cai Xiaofeng, Wang Huiyuan, Wu Bin, Yu Xiang, Shi Tianming   +12 more
wiley   +1 more source

CSANet: Channel and Spatial Mixed Attention CNN for Pedestrian Detection

IEEE Access, 2020
Current mainstream pedestrian detectors tend to profit directly from convolutional neural networks (CNNs) that are designed for image classification.
Yunbo Zhang, Pengfei Yi, Dongsheng Zhou, Xin Yang, Deyun Yang, Qiang Zhang, Xiaopeng Wei   +6 more
doaj   +1 more source

Multiscale soft computing-based model of shear strength of steel fibre-reinforced concrete beams [PDF]

, 2023
Saif Alzabeebee, Rwayda Kh. S. Al‐Hamd, Ali Nassr, Mohammed Kareem, Suraparb Keawsawasvong   +4 more
openalex   +1 more source

Real‐World Performance of CSF Kappa Free Light Chains in the 2024 McDonald Criteria

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective Kappa free light chains (KFLCs) in the cerebrospinal fluid (CSF) have a similar performance to CSF‐restricted oligoclonal bands (OCB) for multiple sclerosis (MS) diagnosis. To help with implementation, we set out to resolve several remaining uncertainties: (1) performance in a real‐world cohort and the 2024 McDonald criteria; (2 ...
Maya M. Leibowitz, Ryan Cooper, Stefania Kaninia, Kathryn I. Challis, Will Greenway, Maria Bonello, Mahmoud Elbahnasawi, Deborah T. Shode, Dominika Gajdasik, Victor Iliev, Alison M. E. Whitelegg, Ian Galea   +11 more
wiley   +1 more source

A Scoping Review on Artificial Intelligence–Supported Interventions for Nonpharmacologic Management of Chronic Rheumatic Diseases

Arthritis Care &Research, EarlyView.
This review summarizes artificial intelligence (AI)‐supported nonpharmacological interventions for adults with chronic rheumatic diseases, detailing their components, purpose, and current evidence base. We searched Embase, PubMed, Cochrane, and Scopus databases for studies describing AI‐supported interventions for adults with chronic rheumatic diseases.
Nirali Shah, Alexis Castellanos, Yen Chen, John Piette, Amy Bucher, Susan Murphy   +5 more
wiley   +1 more source

Elitist-opposition-based artificial electric field algorithm for higher-order neural network optimization and financial time series forecasting

Financial Innovation
This study attempts to accelerate the learning ability of an artificial electric field algorithm (AEFA) by attributing it with two mechanisms: elitism and opposition-based learning.
Sarat Chandra Nayak, Satchidananda Dehuri, Sung-Bae Cho   +2 more
doaj   +1 more source