BACKGROUND: Early diagnosis is crucial for reducing disability and improving long-term prognosis in patients with systemic Juvenile Idiopathic Arthritis (sJIA), but it remains a significant challenge. This study aims to identify non-invasive biomarke...
Medical & biological engineering & computing
Jul 9, 2025
Parkinson's disease (PD) is a prevalent neurodegenerative disorder worldwide, often progressing to mild cognitive impairment (MCI) and dementia. Clinical diagnosis of PD mainly depends on characteristic motor symptoms, which can lead to misdiagnosis,...
This paper proposes a new deep learning and machine learning model for detecting deception and suppression jamming in Ublox-M8T receivers operating under GNSS interference. This solution employs XGBoost for real-time classification of jamming signals...
Deep learning has become powerful and yet versatile tool that allows for the extraction of complex patterns from rich datasets. One field that can benefits from this advancement is human gait analysis. Conventional gait analysis requires a specialize...
The study aimed to review the applicability and performance of various Convolutional Neural Network (CNN) models for the identification of periodontal bone loss (PBL) in digital periapical radiographs achieved through classification, detection, and s...
Small (Weinheim an der Bergstrasse, Germany)
Jul 9, 2025
Electronic noses (e-noses) have become indispensable analytical platforms for gas detection. However, conventional e-nose systems face significant limitations in portable and wearable implementations due to their bulk and high-power consumption. Here...
BACKGROUND: It remains unclear whether the existing health care services reflect the HIV care continuum, which underscores the need for integrated care beyond viral suppression.
BACKGROUND: Prostate cancer (PCa) remains a leading global malignancy, yet current diagnostic reliance on prostate-specific antigen (PSA) testing is limited by suboptimal sensitivity and specificity for early-stage detection. The present study aims t...
Neural networks are challenging to apply in domains requiring high reliability due to their black-box nature, and researchers are increasingly focusing on interpreting neural networks. While pursuing neural network performance, most methods often sac...
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