Molecular genetics and genomics : MGG
Jan 21, 2026
Chromosomal abnormality detection is a fundamental task in clinical genetics, as accurate identification of structural and numerical defects is essential for reliable diagnosis and treatment planning. However, many existing learning-based approaches ...
High inter-subject variability and the non-stationary nature of EEG signals pose significant challenges for subject-independent Brain-Computer Interfaces (BCIs) leading to poor model generalization. Differences in neural activity patterns, electrode ...
BACKGROUND: Artificial intelligence (AI)-powered analysis of electrocardiograms (ECGs) is reshaping cardiac diagnostics, offering faster and often more accurate detection of conditions such as arrhythmias and heart failure. However, growing evidence ...
Objective.Motor imagery brain-computer interfaces hold significant promise for neurorehabilitation, yet their performance is often compromised by electroencephalography (EEG) non-stationarity, low signal-to-noise ratios, and severe cross-session vari...
We report the findings of a reimplementation of 18 foundational studies in feature-based machine learning for Android malware detection, published during the period 2013-2023. These studies are reevaluated on a level playing field using a contemporar...
Semantic code clone detection plays an essential role in software maintenance and quality assurance, as it helps uncover fragments of code that express the same logic even when their syntax has been altered or deliberately obfuscated. In this study, ...
High-Voltage Direct Current (HVDC) transmission systems require fast and reliable fault diagnosis to ensure secure and stable operation. However, existing methods, including conventional Convolutional Neural Networks (CNNs), often suffer from limited...
Image Quality Assessment (IQA) plays a critical role in image-based decision-making systems, especially in domains requiring high diagnostic precision. Effective feature information is a prerequisite for the high performance of machine learning metho...
This study aimed to develop and evaluate a deep learning algorithm for detecting and classifying intrasinus calcifications on paranasal sinus (PNS) computed tomography (CT) for the diagnosis of fungal sinusitis and differentiation of fungal and non-f...
Predicting the steering angle of robots is a core challenge in autonomous navigation. This paper proposes a novel end-to-end prediction network that integrates non-local attention and lane line guidance mechanisms to significantly reduce computationa...
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