Knee injuries are common in several people, frequently controlling for significant injuries and health care costs. This article explains the role of personalized exercise prescriptions in preventing knee injuries. For this purpose, we used the multic...
Deep convolutional neural networks (CNNs) have seen significant growth in medical image classification applications due to their ability to automate feature extraction, leverage hierarchical learning, and deliver high classification accuracy. However...
Accurate Lung cancer (LC) identification is a big medical problem in the AI-based healthcare systems. Various deep learning-based methods have been proposed for Lung cancer diagnosis. In this study, we proposed a Deep learning techniques-based integr...
Deep learning methods have achieved remarkable progress in network intrusion detection. However, their performance often deteriorates significantly in real-world scenarios characterized by limited attack samples and substantial domain shifts. To addr...
In open environments, complex and variable backgrounds and dense multi-scale targets are two key challenges for crowd counting. Due to the reliance on supervised learning with labeled data, current methods struggle to adapt to crowd detection in comp...
Text classification plays an essential role in natural language processing and is commonly used in tasks like categorizing news, sentiment analysis, and retrieving relevant information. [0pc][-9pc]Please check and confirm the inserted city and countr...
Information technology has significantly impacted society. IoT and its specialized variant, IoMT, enable remote patient monitoring and improve healthcare. While it contributes to improving healthcare services, it may pose significant security challen...
This work aims to promote early and accurate diagnosis of Temporal Lobe Epilepsy (TLE) by developing state-of-the-art deep learning techniques, with the goal of minimizing the consequences of epilepsy on individuals and society. Current approaches fo...
Spectrochimica acta. Part A, Molecular and biomolecular spectroscopy
Jul 1, 2025
PURPOSE: Machine-learning-powered label-free infrared spectroscopic methods offer significant potential for diagnostic and biomedical applications. However, their applications have been limited by spectral noise, where critical features are often obs...
Early prediction and warning of occupational noise-induced hearing loss (NIHL) in workers is critical. This study aimed to explore the role of risk factors and their variable types to NIHL prediction through machine learning (ML) techniques. Data on ...
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