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Attention-Like Multimodality Fusion With Data Augmentation for Diagnosis of Mental Disorders Using MRI.
IEEE transactions on neural networks and learning systems
Jun 3, 2024
The globally rising prevalence of mental disorders leads to shortfalls in timely diagnosis and therapy to reduce patients' suffering. Facing such an urgent public health problem, professional efforts based on symptom criteria are seriously overstretc...
BAI-Net: Individualized Anatomical Cerebral Cartography Using Graph Neural Network.
IEEE transactions on neural networks and learning systems
Jun 3, 2024
Brain atlas is an important tool in the diagnosis and treatment of neurological disorders. However, due to large variations in the organizational principles of individual brains, many challenges remain in clinical applications. Brain atlas individual...
Anatomy-Guided Spatio-Temporal Graph Convolutional Networks (AG-STGCNs) for Modeling Functional Connectivity Between Gyri and Sulci Across Multiple Task Domains.
IEEE transactions on neural networks and learning systems
Jun 3, 2024
The cerebral cortex is folded as gyri and sulci, which provide the foundation to unveil anatomo-functional relationship of brain. Previous studies have extensively demonstrated that gyri and sulci exhibit intrinsic functional difference, which is fur...
Prediction of Achilles Tendon Force During Common Motor Tasks From Markerless Video.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 3, 2024
Remodeling of the Achilles tendon (AT) is partly driven by its mechanical environment. AT force can be estimated with neuromusculoskeletal (NMSK) modeling; however, the complex experimental setup required to perform the analyses confines use to the l...
Deep Learning for Electromyographic Lower-Limb Motion Signal Classification Using Residual Learning.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Jun 3, 2024
Electromyographic (EMG) signals have gained popularity for controlling prostheses and exoskeletons, particularly in the field of upper limbs for stroke patients. However, there is a lack of research in the lower limb area, and standardized open-sourc...
Scoring facial attractiveness with deep convolutional neural networks: How training on standardized images reduces the bias of facial expressions.
Orthodontics & craniofacial research
Jun 2, 2024
OBJECTIVE: In many medical disciplines, facial attractiveness is part of the diagnosis, yet its scoring might be confounded by facial expressions. The intent was to apply deep convolutional neural networks (CNN) to identify how facial expressions aff...
Deep learning-based quantification of osteonecrosis using magnetic resonance images in Gaucher disease.
Bone
Jun 2, 2024
Gaucher disease is one of the most common lysosomal storage disorders. Osteonecrosis is a principal clinical manifestation of Gaucher disease and often leads to joint collapse and fractures. T1-weighted (T1w) modality in MRI is widely used to monitor...
Automatic Recognition of Auditory Brainstem Response Waveforms Using a Deep Learning-Based Framework.
Otolaryngology--head and neck surgery : official journal of American Academy of Otolaryngology-Head and Neck Surgery
Jun 1, 2024
OBJECTIVE: Recognition of auditory brainstem response (ABR) waveforms may be challenging, particularly for older individuals or those with hearing loss. This study aimed to investigate deep learning frameworks to improve the automatic recognition of ...
EEG based functional connectivity in resting and emotional states may identify major depressive disorder using machine learning.
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Jun 1, 2024
OBJECTIVE: Disrupted brain network connectivity underlies major depressive disorder (MDD). Altered EEG based Functional connectivity (FC) with Emotional stimuli in major depressive disorder (MDD) in addition to resting state FC may help in improving ...
Relationships between minerals' intake and blood homocysteine levels based on three machine learning methods: a large cross-sectional study.
Nutrition & diabetes
Jun 1, 2024
BACKGROUND: Blood homocysteine (Hcy) level has become a sensitive indicator in predicting the development of cardiovascular disease. Studies have shown an association between individual mineral intake and blood Hcy levels. The effect of mixed mineral...
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