Precision and timeliness in the detection of plant diseases are important to limit crop losses and maintain global food security. Much work has been performed to detect plant diseases using deep learning methods. However, deep learning techniques dem...
European journal of trauma and emergency surgery : official publication of the European Trauma Society
Jul 21, 2025
PURPOSE: Convolutional Neural Networks (CNNs) have shown promise in fracture detection, but their ability to improve surgeons' inconsistent fracture classification remains unstudied. Therefore, our aim was create and (externally) validate the perform...
BACKGROUND: Child malnutrition represents a critical global public health issue and it is characterised by high prevalence and severe long-term consequences for growth and development. A better understanding of its contributory factors is essential t...
This study aims to enhance the accuracy of pneumonia diagnosis from x-ray images by developing a model that integrates Vision Transformer (ViT) and Graph Convolutional Networks (GCN) for improved feature extraction and diagnostic performance. The ViT...
Modern sustainable farming demands precise water management techniques, particularly for crops like potatoes that require high-quality irrigation to ensure optimal growth. This study presents a novel hybrid metaheuristic framework that combines Dippe...
The rapid development of edge computing and artificial intelligence has brought growing interest in collaborative training. While prior research has addressed technical aspects of resource allocation, less attention has been paid to the underlying ec...
The dynamical growth of cyber threats in IoT setting requires smart and scalable intrusion detection systems. In this paper, a Lean-based hybrid Intrusion Detection framework using Particle Swarm Optimization and Genetic Algorithm (PSO-GA) to select ...
BACKGROUND: Identification of drug target interactions (DTI) is an important part of the drug discovery process. Since prediction of DTI using laboratory tests is time consuming and laborious, automated tools using computational intelligence (CI) tec...
Fertility preferences significantly influence population dynamics and reproductive health outcomes, particularly in low-resource settings, such as Somalia, where high fertility rates and limited healthcare infrastructure pose significant challenges. ...
Current methods for detecting soybean fungal contamination are often destructive, time-consuming, and labor-intensive. This study proposed an efficient approach by fusing visible and near-infrared (VNIR) and short-wave infrared (SWIR) hyperspectral i...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.