While deep learning has enabled the decoding of language from intracranial brain recordings, achieving this with non-invasive recordings remains an open challenge. We introduce a deep learning pipeline to decode individual words from electro- (EEG) a...
Large Language Models (LLMs) offer a framework for understanding language processing in the human brain. Unlike traditional models, LLMs represent words and context through layered numerical embeddings. Here, we demonstrate that LLMs' layer hierarchy...
INTRODUCTION: Dysphagia, or difficulty in swallowing, significantly impacts the quality of life of the affected individuals. Diagnostic approaches, including video fluoroscopic swallowing studies and flexible endoscopic evaluation of swallowing, are ...
INTRODUCTION: Obesity disproportionately affects ethnic minority populations due to structural inequalities, such as limited access to healthy food, inadequate healthcare and systemic racism. Universal weight management programmes often fail to meet ...
BACKGROUND: Pain and emotional distress are prevalent concerns in pediatric hospital care, underscoring the need for safe and evidence-based nonpharmacological interventions. Socially assistive robots (SARs) are innovative tools that alleviate pain a...
BACKGROUND: Colon cancer is a leading cause of cancer-related deaths worldwide, with survival influenced by risk factors, treatment type, and patient characteristics. Traditional statistical models, such as Kaplan-Meier curves, have been widely used ...
Effective control of bipedal postures relies on sensory inputs from the past, which encode dynamic changes in the spatial properties of our movement over time. To uncover how the spatial and temporal properties of an upright posture interact in the p...
Autonomy is a fundamental ethical principle in artificial intelligence (AI) ethics. Current discussions regarding autonomy-related risks in human-AI interaction, as well as potential mitigation strategies, have mainly focused on recommendation system...
Bone age assessment and adult height prediction are essential for evaluating pediatric growth. Traditional methods rely on manual radiographic interpretation, which is subjective, time-consuming, and prone to inter-observer variability. This study pr...
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