Latest AI and machine learning research in neurology for healthcare professionals.
This paper introduces a topological framework for interpreting the internal representations of Multilayer Perceptrons (MLPs). We construct a simplicial tower, a sequence of simplicial complexes connected by simplicial maps, that captures how data topology evolves across network layers. Our approach enables bi-persistence analysis: layer persistence tracks topological features within each layer a...
The integration of brain-computer interfaces (BCIs), in particular electroencephalography (EEG), with artificial intelligence (AI) has shown tremendous promise in decoding human cognition and behavior from neural signals. In particular, the rise of multimodal AI models have brought new possibilities that have never been imagined before. Here, we present EgoBrain --the world's first large-scale, ...
Steady-State Visual Evoked Potential is a brain response to visual stimuli flickering at constant frequencies. It is commonly used in brain-computer...
Previous works in the literature apply 3D spatial-only models on 4D functional MRI data leading to possible sub-par feature extraction to be used fo...
Large Language Models (LLMs) trained on massive data capture rich information embedded in the training data. However, this also introduces the risk ...
Large Language Models (LLMs) trained on massive data capture rich information embedded in the training data. However, this also introduces the risk ...
The periprosthetic acetabular osteotomy (PAO) is a commonly used technique in orthopedics for treating developmental hip dysplasia and hip dislocation...
Quantitative T1 and T2 mapping is a useful tool to assess properties of healthy and diseased tissues. However, clinical diagnostic imaging remains dom...
Protein aggregation is associated with a spectrum of neurodegenerative diseases. Although many small ligands have been found to modulate or inhibit pr...
There is an urgent need for the precise prediction of cerebral amyloidosis using noninvasive and accessible indicators to facilitate the early diagnos...
OBJECTIVES: Late-life depression often overlaps with neurodegenerative diseases leading to diagnostic and treatment challenges for neuropsychiatrists....
OBJECTIVE: Software engineering innovations have led to the development of virtual surgical planning software (VSPS) for deformity correction. VSPS us...
Electroencephalogram (EEG) signals pose a challenge to emotion recognition (ER) tasks due to their complexity and individual differences. Conventional...
Neural networks are responsible for processing sensory stimuli and driving the synaptic activity required for brain function and behavior. This comput...
Prosthetic rehabilitation after amputation poses significant challenges, often due to functional limitations, residual limb pain (RLP), and phantom li...
OBJECTIVE: Stroke is a leading cause of morbidity and disability worldwide. Post-stroke cognitive impairment (PSCI) significantly affects long-term pr...
Tension-type headache (TTH) is a primary headache with the highest prevalence. Previous studies have revealed the local brain abnormalities of TTH pat...
Adeno-associated virus (AAV) is a non-enveloped DNA virus infecting a wide variety of species, tissues, and cell types, which is recognized as a safe ...
Cancer pain management (CPM) is crucial in oncology care, with current approaches including pharmacotherapy, radiotherapy, chemotherapy, nerve blocks,...
Proteomic studies have been instrumental in identifying brain, cerebrospinal fluid and plasma proteins associated with Alzheimer's disease (AD). Here,...