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Automated radiography assessment of ankle joint instability using deep learning.

Scientific reports
This study developed and evaluated a deep learning (DL)-based system for automatically measuring talar tilt and anterior talar translation on weight-bearing ankle radiographs, which are key parameters in diagnosing ankle joint instability. The system...

Development of an artificial intelligence powered software for automated analysis of skeletal muscle ultrasonography.

Scientific reports
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
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
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...

Deep learning for quality assessment of axial T2-weighted prostate MRI: a tool to reduce unnecessary rescanning.

European radiology experimental
BACKGROUND: T2-weighted images are a critical component of prostate magnetic resonance imaging (MRI), and it would be useful to automatically assess image quality (IQ) on a patient-specific basis without radiologist oversight.

Predicting Visual Acuity after Retinal Vein Occlusion Anti-VEGF Treatment: Development and Validation of an Interpretable Machine Learning Model.

Journal of medical systems
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
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...

Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk.

PloS one
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...

Urban walkability through different lenses: A comparative study of GPT-4o and human perceptions.

PloS one
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...