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Development of an artificial intelligence powered software for automated analysis of skeletal muscle ultrasonography.
Scientific reports
Apr 29, 2025
Muscle ultrasound has high utility in clinical practice and research; however, the main challenges are the training and time required for manual analysis to achieve objective quantification of muscle size and quality. We aimed to develop and validate...
Human-generative AI collaboration enhances task performance but undermines human's intrinsic motivation.
Scientific reports
Apr 29, 2025
In a series of four online experimental studies (total N = 3,562), we investigated the performance augmentation effect and psychological deprivation effect of human-generative AI (GenAI) collaboration in professional settings. Our findings consistent...
Health-Promoting Effects and Everyday Experiences With a Mental Health App Using Ecological Momentary Assessments and AI-Based Ecological Momentary Interventions Among Young People: Qualitative Interview and Focus Group Study.
JMIR mHealth and uHealth
Apr 29, 2025
BACKGROUND: Considering the high prevalence of mental health conditions among young people and the technological advancements of artificial intelligence (AI)-based approaches in health services, mobile health (mHealth) apps for mental health are a pr...
Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.
Journal of medical systems
Apr 29, 2025
Accurate prediction of post-treatment visual acuity in macular edema secondary to retinal vein occlusion (RVO-ME) is critical for optimizing anti-VEGF therapy and improving clinical outcomes. While machine learning (ML) has shown promise in ophthalmi...
From pixels to prognosis: leveraging radiomics and machine learning to predict IDH1 genotype in gliomas.
Neurosurgical review
Apr 29, 2025
Gliomas are the most common primary tumors of the central nervous system, and advances in genetics and molecular medicine have significantly transformed their classification and treatment. This study aims to predict the IDH1 genotype in gliomas using...
A deep-learning algorithm using real-time collected intraoperative vital sign signals for predicting acute kidney injury after major non-cardiac surgeries: A modelling study.
PLoS medicine
Apr 29, 2025
BACKGROUND: Postoperative acute kidney injury (PO-AKI) prediction models for non-cardiac major surgeries typically rely solely on preoperative clinical characteristics.
Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk.
PloS one
Apr 29, 2025
In fast-paced urban environments, Citywalk has emerged as a key leisure activity for urban residents to alleviate stress and enhance emotional well-being. From the perspective of virtual-physical interaction, this study integrates social media data w...
Using artificial intelligence-based software for an unbiased discrimination of immune cell subtypes in the fracture hematoma and bone marrow of non-osteoporotic and osteoporotic mice.
PloS one
Apr 29, 2025
It is well established that the early inflammatory response following fracture is essential for initiating subsequent bone regeneration. An imbalance in inflammation, whether within the innate or adaptive immune response, can result in impaired fract...
Urban walkability through different lenses: A comparative study of GPT-4o and human perceptions.
PloS one
Apr 29, 2025
Urban environments significantly shape our well-being, behavior, and overall quality of life. Assessing urban environments, particularly walkability, has traditionally relied on computer vision and machine learning algorithms. However, these approach...
Topology-Guided Graph Masked Autoencoder Learning for Population-Based Neurodevelopmental Disorder Diagnosis.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
Apr 29, 2025
Exploring the pathogenic mechanisms of brain disorders within population is an important research in the field of neuroscience. Existing methods either combine clinical information to assist analysis or use data augmentation for sample expansion, ign...
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