AIMC Topic: Humans

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Estimating the predictability of questionable open-access journals.

Science advances
Questionable journals threaten global research integrity, yet manual vetting can be slow and inflexible. Here, we explore the potential of artificial intelligence (AI) to systematically identify such venues by analyzing website design, content, and p...

A heart failure classification model from radial artery pulse wave using LSTM neural networks.

BMC medical informatics and decision making
BACKGROUND: Heart failure (HF) represents a pressing global health issue demanding innovative and accessible approaches for early detection. Non-invasive, rapid, and cost-effective techniques utilizing deep learning (DL) hold significant promise for ...

Optimizing ambulance location based on road accident data in Rwanda using machine learning algorithms.

International journal of health geographics
BACKGROUND: The optimal placement of ambulances is critical for ensuring timely emergency medical responses, especially in regions with high accident frequencies. In Rwanda, where road accidents are a leading cause of injury and death, the strategic ...

Development and validation of a deep learning model for early detection and screening of diabetic retinopathy.

BMC medical informatics and decision making
Early diagnosis and screening of diabetic retinopathy (DR) are crucial for reducing medical burdens and conserving healthcare resources. This study introduces an advanced AI-assisted recognition system designed to enhance the detection of DR lesions ...

Deep learning-based automatic facial symmetry scoring in peripheral facial palsy.

Scientific reports
Unilateral peripheral facial palsy (PFP) results in facial asymmetry and functional impairment, reducing quality of life. Accurate, objective assessment is vital for monitoring and rehabilitation. This study presents an automated method utilizes stan...

Cox proportional hazards model with Bayesian neural network for survival prediction.

Scientific reports
Survival analysis plays a crucial aspect in medical research and other domains where understanding the time-to-events is paramount. In this study, we present a novel approach for estimating survival outcomes that combines Bayesian neural networks wit...

Performance of mental health chatbot agents in detecting and managing suicidal ideation.

Scientific reports
Advances in artificial intelligence (AI) technologies sparked a rapid development of smartphone applications designed to help individuals experiencing mental health problems through an AI-powered chatbot agent. However, the safety of such agents when...

Hierarchical query design and distributed attention in transformer for player group activity recognition in sports analysis.

Scientific reports
Group activity recognition in sports analysis is a critical challenge in computer vision, requiring robust modeling of complex player interactions and dynamic scenarios. Existing approaches predominantly rely on region-based features and two-stage pi...

Deep learning for classifying imaging patterns of interstitial lung disease associated with idiopathic inflammatory myopathies.

Scientific reports
Diagnosing and classifying the imaging patterns of idiopathic inflammatory myopathies-associated interstitial lung disease (IIM-ILD) is a crucial but challenging task requiring specialized physicians' expertise. This study aims to develop and validat...

All-flexible chronoepifluidic nanoplasmonic patch for label-free metabolite profiling in sweat.

Nature communications
Wearable sensors allow non-invasive monitoring of sweat metabolites, but their reliance on molecular recognition elements limits both physiological coverage and temporal resolution. Here we report an all-flexible chronoepifluidic surface-enhanced Ram...