This study aims to develop an intelligent system leveraging Internet of Thing (IoT) technology to enhance the precision of youth physical training monitoring and improve training outcomes. A wearable device incorporating Micro Electro Mechanical Syst...
Post-COVID-19, depression rates have risen sharply, increasing the need for early diagnosis using electroencephalogram (EEG) and deep learning. To tackle this, we developed a cloud-based computer-aided depression diagnostic (CCADD) system that utiliz...
Hypoxemia is a common complication associated with anesthesia in painless gastroscopy. With the aging of the social population, the number of cases of hypoxemia among middle-aged and elderly patients is increasing. However, tools for predicting hypox...
This study aimed to develop a predictive model integrating clinical, radiomics, and deep learning (DL) features of hyperattenuated imaging markers (HIM) from computed tomography scans immediately following mechanical thrombectomy (MT) to predict hemo...
European journal of trauma and emergency surgery : official publication of the European Trauma Society
May 23, 2025
BACKGROUND: Severe bleeding is a leading cause of ICU admission and mortality. Fibrinogen plays a crucial role in prognosis, yet optimal thresholds and supplementation targets remain unclear.
BACKGROUND: Young adults experience stressors in their transition to adulthood and are at increased risk of mental ill-health. This risk is compounded by young adults' low levels of mental health literacy and limited competencies in implementing stra...
BACKGROUND: This study investigated the cost-effectiveness and clinical impact of the 3E model (education, empowerment, and economy) in diabetes management using advanced machine learning techniques.
Children often learn the meanings of nouns before they grasp the meanings of verbs. This discrepancy could arise from differences in the complexity of visual characteristics for categories that language describes, the inherent structure of language, ...
AIM: This study aimed to explore the efficacy of MRI-based radiomics models, employing various machine learning techniques, in the preoperative prediction of the digital subtraction angiography (DSA) classification of venous malformations (VMs).
International journal of molecular sciences
May 22, 2025
Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options, and early detection remains challenging due to the lack of reliable non-invasive biomarkers. This study investigated plasma and urine circulating tumor deo...
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