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GDM-BC: Non-invasive body composition dataset for intelligent prediction of Gestational Diabetes Mellitus.
Computers in biology and medicine
Apr 23, 2025
Gestational Diabetes Mellitus (GDM) refers to any degree of impaired glucose tolerance with onset or first recognition during pregnancy. As a high-prevalence disease, GDM damages the health of both pregnant women and fetuses in the short and long ter...
Validating Emotion Analysis on Social Media Text for Detecting Psychological Distress: A Cross-Sectional Survey.
Issues in mental health nursing
Apr 23, 2025
This study investigates the relationship between self-reported psychological distress and emotions in social media posts, using a deep learning-based emotion analysis model. A cross-sectional design was used, collecting data from Instagram and Thread...
Deep learning-based post hoc denoising for 3D volume-rendered cardiac CT in mitral valve prolapse.
The international journal of cardiovascular imaging
Apr 23, 2025
We hypothesized that deep learning-based post hoc denoising could improve the quality of cardiac CT for the 3D volume-rendered (VR) imaging of mitral valve (MV) prolapse. We aimed to evaluate the quality of denoised 3D VR images for visualizing MV pr...
Deep learning approach in undergraduate nursing students and their relationship with learning outcomes: A latent profile analysis.
Nurse education in practice
Apr 23, 2025
BACKGROUND: Deep learning approach plays a pivotal role in nursing education, equipping students with the critical thinking skills and knowledge necessary to address complex clinical challenges. However, nursing students exhibit diverse approaches to...
Evaluating and mitigating bias in AI-based medical text generation.
Nature computational science
Apr 23, 2025
Artificial intelligence (AI) systems, particularly those based on deep learning models, have increasingly achieved expert-level performance in medical applications. However, there is growing concern that such AI systems may reflect and amplify human ...
Dynamic Hierarchical Convolutional Attention Network for Recognizing Motor Imagery Intention.
IEEE transactions on cybernetics
Apr 23, 2025
The neural activity patterns of localized brain regions are crucial for recognizing brain intentions. However, existing electroencephalogram (EEG) decoding models, especially those based on deep learning, predominantly focus on global spatial feature...
The predictive role of identifying frailty in assessing the need for palliative care in the elderly: the application of machine learning algorithm.
Journal of health, population, and nutrition
Apr 23, 2025
BACKGROUND: Palliative care is a key component of integrated care to improve care quality and reduce hospitalization costs for patients with chronic obstructive pulmonary disease (COPD). This study aims to use machine learning algorithms to create an...
An integrated machine learning model of transcriptomic genes in multi-center chronic obstructive pulmonary disease reveals the causal role of TIMP4 in airway epithelial cell.
Respiratory research
Apr 23, 2025
BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous syndrome, resulting in inconsistent findings across studies. Identifying a core set of genes consistently involved in COPD pathogenesis, independent of patient variability, i...
Random forest algorithm for predicting tobacco use and identifying determinants among pregnant women in 26 sub-Saharan African countries: a 2024 analysis.
BMC public health
Apr 23, 2025
INTRODUCTION: Tobacco use during pregnancy is a significant public health concern, associated with adverse maternal and neonatal outcomes. Despite its critical importance, comprehensive data on tobacco use among pregnant women in sub-Saharan Africa i...
Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions.
BMC medical education
Apr 23, 2025
BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.
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