Latest AI and machine learning research in head trauma for healthcare professionals.
Neural network training tends to exploit the simplest features as shortcuts to greedily minimize training loss. However, some of these features might be spuriously correlated with the target labels, leading to incorrect predictions by the model. Several methods have been proposed to address this issue. Focusing on suppressing the spurious correlations with model training, they not only incur add...
The success of deep learning (DL) is often achieved with large models and high complexity during both training and post-training inferences, hindering training in resource-limited settings. To alleviate these issues, this paper introduces a new framework dubbed ``coded deep learning'' (CDL), which integrates information-theoretic coding concepts into the inner workings of DL, to significantly co...
Network control theory (NCT) has recently been utilized in neuroscience to facilitate our understanding of brain stimulation effects. A particularly...
The diffusion models are widely used for image and video generation, but their iterative generation process is slow and expansive. While existing di...
The low-altitude economy (LAE) plays an indispensable role in cargo transportation, healthcare, infrastructure inspection, and especially post-disas...
Healthy brain networks usually show highly efficient information communication and self-sustained oscillation abilities. However, how the brain netw...
Domain-adaptive post-training of large language models (LLMs) has emerged as a promising approach for specialized domains such as medicine and finan...
Stroke is a leading cause of disability and death due to the brain’s limited ability to regenerate damaged neural circuits. To date, stroke patients h...
Transcranial Magnetic Stimulation (TMS) with simultaneous Electroencephalogram (TMS-EEG) allows assessing the neurophysiological properties of cortica...
Advancements in the treatment of Disorders of Consciousness have seen significant progress with per-turbative techniques and pharmacological therapies...
Given the well-established structural and functional changes in the aging brain, it is widely assumed that cognitive aging is primarily driven by robu...
The parsing of sensory information into discrete topographic domains is a fundamental principle of sensory processing. In the auditory cortex, these d...
Post-mortem diffusion MRI plays a key role in investigative pipelines to characterise tissue microstructure, with long scan times facilitating the acq...
The application of artificial intelligence (AI)/machine learning (ML) to MRI can be a powerful tool to streamline clinical decision-making, yet variab...
Immoral decisions, which engage both cognitive control and reward system, bring both cognitive and neural consequences. However, how dishonesty has an...
Post-traumatic osteoarthritis (PTOA) is a common sequela to joint injury in both humans and companion animal species such as horses and dogs. Despite ...
Astrocytes regulate the activity of nearby neurons so disruption of astrocyte calcium dynamics by traumatic brain injury (TBI) could have profound con...
Hydrogen-deuterium exchange/mass spectrometry (HX/MS) is a rapidly expanding technique used to investigate protein conformational ensembles. The growi...
Histology is the cornerstone of clinical pathology and an essential tool for many areas of medicine. Nevertheless, conventional histological methods, ...
Genomic functions arise from nucleotide sequences and their overlapping k-mers – subsequences whose contributions depend on their composition, positio...