BACKGROUND: Diabetic foot ulcers (DFUs) constitute a significant complication among individuals with diabetes and serve as a primary cause of nontraumatic lower-extremity amputation (LEA) within this population. We aimed to develop machine learning (...
OBJECTIVES: Accurate determination of gastrointestinal tumor malignancy is a crucial focus of clinical research. Constructing coagulation index models using big data is feasible to achieve this goal. This study builds various prediction models throug...
BACKGROUND: The unique anatomical characteristics and blood supply of the rectosigmoid junction confer particular significance to its physiological functions and clinical surgeries. However, research on the prognosis of rectosigmoid junction cancer (...
ObjectiveEndovascular aneurysm repair (EVAR) has become a preferred method for treating abdominal aortic aneurysms (AAA) due to its minimally invasive approach. However, identifying factors that influence long-term patient outcomes is crucial for imp...
This study explores using dual-modal sensory data and machine learning to objectively identify Attention-Deficit/Hyperactivity Disorder (ADHD), a neurodevelopmental disorder traditionally diagnosed through subjective clinical evaluations. Six machine...
Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
Mar 24, 2025
OBJECTIVE: This study investigates the neurophysiological outcomes of combining robot-assisted gait training (RAGT) with active transcranial direct current stimulation (tDCS) on individuals with spinal cord injury (SCI).
AIM: To train a machine learning algorithm to identify eye movement from electrooculography (EOG) in cardiac arrest (CA) patients. Neuroprognostication of comatose post-CA patients is challenging, requiring novel biomarkers to guide decision making. ...
This study examines the complex relationships among artificial intelligence (AI) adoption in organizations, employee work overload, and pro-environmental behavior at work (PEBW), while examining the moderating role of self-efficacy in AI learning. Dr...
The temporal order of a sequence of events has been thought to be reflected in the ordered firing of neurons at different phases of theta oscillations. Here we assess this by measuring single neuron activity (1,420 neurons) and local field potentials...
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