BACKGROUND: Glioma is a common primary malignant brain tumor. This study aimed to develop a predictive model for glioma risk by these screened key SNPs in the Chinese Han population.
BACKGROUND: Stroke is a leading cause of long-term disability, with lower limb dysfunction being a common sequela that significantly impacts patients' mobility and quality of life. Robotic-assisted training has emerged as a promising intervention for...
BACKGROUND: Lower limb exoskeleton rehabilitation robot is a new technology to improve the lower limb motor function of stroke patients. Recovery of motor function after stroke is closely related to neuroplasticity in the motor cortex and associated ...
PURPOSE: This study aims to evaluate the survival and mortality rates of stroke patients after receiving enteral nutrition, and to explore factors influencing long-term survival. With an aging society, nutritional management of stroke patients has be...
BACKGROUND: Vascular disease in aging populations spans a wide range of disorders including strokes, circulation disorders and hypertension. As individuals age, vascular disorders co-occur and hence exert combined effects. In the present study we int...
BACKGROUND: Parkinson's disease (PD), a prevalent neurodegenerative disorder in the aging population, poses significant challenges in unraveling its pathogenesis and progression. A key area of investigation is the disruption of oncological metabolic ...
BACKGROUND AND PURPOSE: White matter hyperintensities in brain MRI are key indicators of various neurological conditions, and their accurate segmentation is essential for assessing disease progression. This study aims to evaluate the performance of a...
Parkinson's disease (PD) is a neurodegenerative disease affecting millions of people around the world. Conventional PD detection algorithms are generally based on first and second-generation artificial neural network (ANN) models which consume high e...
BACKGROUND: ICU-acquired weakness (ICU-AW) is a common complication among ICU patients. We used machine learning techniques to construct an ICU-AW inflammatory factor prediction model to predict the risk of disease development and reduce the incidenc...