This paper demonstrates how artificial-intelligence language analysis can inform understanding of human-nature relationships and other social phenomena. We demonstrate three techniques by investigating relationships within the popular word2vec word e...
BACKGROUND: Predicting functional impairment after intracerebral hemorrhage (ICH) provides valuable information for planning of patient care and rehabilitation strategies. Current prognostic tools are limited in making long term predictions and requi...
Skeletal muscle is a vital organ that promotes human movement and maintains posture. Accurate assessment of muscle strength is helpful to provide valuable insights for athletes' rehabilitation and strength training. However, traditional techniques re...
Valproic acid (VPA) is a primary medication for epilepsy, yet its hepatotoxicity consistently raises concerns among individuals. This study aims to establish an automated machine learning (autoML) model for forecasting the risk of abnormal increase o...
International journal of computer assisted radiology and surgery
Jun 16, 2024
PURPOSE: MRI-derived brain volume loss (BVL) is widely used as neurodegeneration marker. SIENA is state-of-the-art for BVL measurement, but limited by long computation time. Here we propose "BrainLossNet", a convolutional neural network (CNN)-based m...
Dementia is a progressive neurological disorder that affects the daily lives of older adults, impacting their verbal communication and cognitive function. Early diagnosis is important to enhance the lifespan and quality of life for affected individua...
Virchows Archiv : an international journal of pathology
Jun 15, 2024
Histological assessment of autoimmune hepatitis (AIH) is challenging. As one of the possible results of these challenges, nonclassical features such as bile-duct injury stays understudied in AIH. We aim to develop a deep learning tool (artificial int...
Pattern recognition based on network connections has recently been applied to the brain-computer interface (BCI) research, offering new ideas for emotion recognition using Electroencephalogram (EEG) signal. However unified standards are currently lac...
BACKGROUND: Machine learning clustering of patients with ST-elevation acute myocardial infarction (STEMI) may provide important insights into their risk profile, management and prognosis.
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